Search results for: series filter.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3363

Search results for: series filter.

3183 Forecasting Performance Comparison of Autoregressive Fractional Integrated Moving Average and Jordan Recurrent Neural Network Models on the Turbidity of Stream Flows

Authors: Daniel Fulus Fom, Gau Patrick Damulak

Abstract:

In this study, the Autoregressive Fractional Integrated Moving Average (ARFIMA) and Jordan Recurrent Neural Network (JRNN) models were employed to model the forecasting performance of the daily turbidity flow of White Clay Creek (WCC). The two methods were applied to the log difference series of the daily turbidity flow series of WCC. The measurements of error employed to investigate the forecasting performance of the ARFIMA and JRNN models are the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The outcome of the investigation revealed that the forecasting performance of the JRNN technique is better than the forecasting performance of the ARFIMA technique in the mean square error sense. The results of the ARFIMA and JRNN models were obtained by the simulation of the models using MATLAB version 8.03. The significance of using the log difference series rather than the difference series is that the log difference series stabilizes the turbidity flow series than the difference series on the ARFIMA and JRNN.

Keywords: auto regressive, mean absolute error, neural network, root square mean error

Procedia PDF Downloads 241
3182 Degree of Approximation by the (T.E^1) Means of Conjugate Fourier Series in the Hölder Metric

Authors: Kejal Khatri, Vishnu Narayan Mishra

Abstract:

We compute the degree of approximation of functions\tilde{f}\in H_w, a new Banach space using (T.E^1) summability means of conjugate Fourier series. In this paper, we extend the results of Singh and Mahajan which in turn generalizes the result of Lal and Yadav. Some corollaries have also been deduced from our main theorem and particular cases.

Keywords: conjugate Fourier series, degree of approximation, Hölder metric, matrix summability, product summability

Procedia PDF Downloads 378
3181 Digital Watermarking Based on Visual Cryptography and Histogram

Authors: R. Rama Kishore, Sunesh

Abstract:

Nowadays, robust and secure watermarking algorithm and its optimization have been need of the hour. A watermarking algorithm is presented to achieve the copy right protection of the owner based on visual cryptography, histogram shape property and entropy. In this, both host image and watermark are preprocessed. Host image is preprocessed by using Butterworth filter, and watermark is with visual cryptography. Applying visual cryptography on water mark generates two shares. One share is used for embedding the watermark, and the other one is used for solving any dispute with the aid of trusted authority. Usage of histogram shape makes the process more robust against geometric and signal processing attacks. The combination of visual cryptography, Butterworth filter, histogram, and entropy can make the algorithm more robust, imperceptible, and copy right protection of the owner.

Keywords: digital watermarking, visual cryptography, histogram, butter worth filter

Procedia PDF Downloads 321
3180 A Posteriori Trading-Inspired Model-Free Time Series Segmentation

Authors: Plessen Mogens Graf

Abstract:

Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

Procedia PDF Downloads 104
3179 Segmenting 3D Optical Coherence Tomography Images Using a Kalman Filter

Authors: Deniz Guven, Wil Ward, Jinming Duan, Li Bai

Abstract:

Over the past two decades or so, Optical Coherence Tomography (OCT) has been used to diagnose retina and optic nerve diseases. The retinal nerve fibre layer, for example, is a powerful diagnostic marker for detecting and staging glaucoma. With the advances in optical imaging hardware, the adoption of OCT is now commonplace in clinics. More and more OCT images are being generated, and for these OCT images to have clinical applicability, accurate automated OCT image segmentation software is needed. Oct image segmentation is still an active research area, as OCT images are inherently noisy, with the multiplicative speckling noise. Simple edge detection algorithms are unsuitable for detecting retinal layer boundaries in OCT images. Intensity fluctuation, motion artefact, and the presence of blood vessels also decrease further OCT image quality. In this paper, we introduce a new method for segmenting three-dimensional (3D) OCT images. This involves the use of a Kalman filter, which is commonly used in computer vision for object tracking. The Kalman filter is applied to the 3D OCT image volume to track the retinal layer boundaries through the slices within the volume and thus segmenting the 3D image. Specifically, after some pre-processing of the OCT images, points on the retinal layer boundaries in the first image are identified, and curve fitting is applied to them such that the layer boundaries can be represented by the coefficients of the curve equations. These coefficients then form the state space for the Kalman Filter. The filter then produces an optimal estimate of the current state of the system by updating its previous state using the measurements available in the form of a feedback control loop. The results show that the algorithm can be used to segment the retinal layers in OCT images. One of the limitations of the current algorithm is that the curve representation of the retinal layer boundary does not work well when the layer boundary is split into two, e.g., at the optic nerve, the layer boundary split into two. This maybe resolved by using a different approach to representing the boundaries, such as b-splines or level sets. The use of a Kalman filter shows promise to developing accurate and effective 3D OCT segmentation methods.

Keywords: optical coherence tomography, image segmentation, Kalman filter, object tracking

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3178 Residual Power Series Method for System of Volterra Integro-Differential Equations

Authors: Zuhier Altawallbeh

Abstract:

This paper investigates the approximate analytical solutions of general form of Volterra integro-differential equations system by using the residual power series method (for short RPSM). The proposed method produces the solutions in terms of convergent series requires no linearization or small perturbation and reproduces the exact solution when the solution is polynomial. Some examples are given to demonstrate the simplicity and efficiency of the proposed method. Comparisons with the Laplace decomposition algorithm verify that the new method is very effective and convenient for solving system of pantograph equations.

Keywords: integro-differential equation, pantograph equations, system of initial value problems, residual power series method

Procedia PDF Downloads 391
3177 Low-Power Digital Filters Design Using a Bypassing Technique

Authors: Thiago Brito Bezerra

Abstract:

This paper presents a novel approach to reduce power consumption of digital filters based on dynamic bypassing of partial products in their multipliers. The bypassing elements incorporated into the multiplier hardware eliminate redundant signal transitions, which appear within the carry-save adders when the partial product is zero. This technique reduces the power consumption by around 20%. The circuit implementation was made using the AMS 0.18 um technology. The bypassing technique applied to the circuits is outlined.

Keywords: digital filter, low-power, bypassing technique, low-pass filter

Procedia PDF Downloads 351
3176 Treatment of Simulated Textile Wastewater Containing Reactive Azo Dyes Using Laboratory Scale Trickling Filter

Authors: Ayesha Irum, Sadia Mumtaz, Abdul Rehman, Iffat Naz, Safia Ahmed

Abstract:

The present study was conducted to evaluate the potential applicability of biological trickling filter system for the treatment of simulated textile wastewater containing reactive azo dyes with bacterial consortium under non-sterile conditions. The percentage decolorization for the treatment of wastewater containing structurally different dyes was found to be higher than 95% in all trials. The stable bacterial count of the biofilm on stone media of the trickling filter during the treatment confirmed the presence, proliferation, dominance and involvement of the added microbial consortium in the treatment of textile wastewater. Results of physicochemical parameters revealed the reduction in chemical oxygen demand (58.5-75.1%), sulphates (18.9-36.5%), and phosphates (63.6-73.0%). UV-Visible and FTIR spectroscopy confirmed decolorization of dye containing wastewater was the ultimate consequence of biodegradation. Toxicological studies revealed the nontoxic nature of degradative metabolites.

Keywords: biodegradation, textile dyes, waste water, trickling filters

Procedia PDF Downloads 394
3175 Model Predictive Control with Unscented Kalman Filter for Nonlinear Implicit Systems

Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

A class of implicit systems is known as a more generalized class of systems than a class of explicit systems. To establish a control method for such a generalized class of systems, we adopt model predictive control method which is a kind of optimal feedback control with a performance index that has a moving initial time and terminal time. However, model predictive control method is inapplicable to systems whose all state variables are not exactly known. In other words, model predictive control method is inapplicable to systems with limited measurable states. In fact, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. It is also usual that output signals are disturbed by process and sensor noises. Hence, it is important to establish a state estimation method for nonlinear implicit systems with taking the process noise and sensor noise into consideration. To this purpose, we apply the model predictive control method and unscented Kalman filter for solving the optimization and estimation problems of nonlinear implicit systems, respectively. The objective of this study is to establish a model predictive control with unscented Kalman filter for nonlinear implicit systems.

Keywords: optimal control, nonlinear systems, state estimation, Kalman filter

Procedia PDF Downloads 167
3174 Strategy of Inventory Analysis with Economic Order Quantity and Quick Response: Case on Filter Inventory for Heavy Equipment in Indonesia

Authors: Lim Sanny, Felix Christian

Abstract:

The use of heavy equipment in Indonesia is always increasing. Cost reduction in procurement of spare parts is the aim of the company. The spare parts in this research are focused in the kind of filters. On the early step, the choosing of priority filter will be studied further by using the ABC analysis. To find out future demand of the filter, this research is using demand forecast by utilizing the QM software for windows. And to find out the best method of inventory control for each kind of filter is by comparing the total cost of Economic Order Quantity and Quick response inventory method. For the three kind of filters which are Cartridge, Engine oil – pn : 600-211-123, Element, Transmission – pn : 424-16-11140, and Element, Hydraulic – pn : 07063-01054, the best forecasting method is Linear regression. The best method for inventory control of Cartridge, Engine oil – pn : 600-211-123 and Element, Transmission – pn : 424-16-11140, is Quick Response Inventory, while the best method for Element, Hydraulic – pn : 07063-01054 is Economic Order Quantity.

Keywords: strategy, inventory, ABC analysis, forecasting, economic order quantity, quick response inventory

Procedia PDF Downloads 336
3173 Enhanced Cytotoxic Effect of Expanded NK Cells with IL12 and IL15 from Leukoreduction Filter on K562 Cell Line Exhibits Comparable Cytotoxicity to Whole Blood

Authors: Abdulbaset Mazarzaei

Abstract:

Natural killer (NK) cells are innate immune effectors that play a pivotal role in combating tumors and infected cells. In recent years, the therapeutic potential of NK cells has gained significant attention due to their remarkable cytotoxic ability. This study focuses on investigating the cytotoxic effect of expanded NK cells enriched with interleukin 12 (IL12) and interleukin 15 (IL15), derived from the leukoreduction filter, on the K562 cell line. Firstly, NK cells were isolated from whole blood samples obtained from healthy volunteers. These cells were subsequently expanded ex vivo using a combination of feeder cells, IL12, and IL15. The expanded NK cells were then harvested and assessed for their cytotoxicity against K562, a well-established human chronic myelogenous leukemia cell line. The cytotoxicity was evaluated using flow cytometry assay. Results demonstrate that the expanded NK cells significantly exhibited enhanced cytotoxicity against K562 cells compared to non-expanded NK cells. Interestingly, the expanded NK cells derived specifically from IL12 and IL15-enriched leukoreduction filters showed a robust cytotoxic effect similar to the whole blood-derived NK cells. These findings suggest that IL12 and IL15 in the leukoreduction filter are crucial in promoting NK cell cytotoxicity. Furthermore, the expanded NK cells displayed relatively similar cytotoxicity profiles to whole blood-derived NK cells, indicating their comparable capability in targeting and eliminating tumor cells. This observation is of significant relevance as expanded NK cells from the leukoreduction filter could potentially serve as a readily accessible and efficient source for adoptive immunotherapy. In conclusion, this study highlights the significant cytotoxic effect of expanded NK cells enriched with IL12 and IL15 obtained from the leukoreduction filter on the K562 cell line. Moreover, it emphasizes that these expanded NK cells exhibit comparable cytotoxicity to whole blood-derived NK cells. These findings reinforce the potential clinical utility of using expanded NK cells from the leukoreduction filter as an effective strategy in adoptive immunotherapy for the treatment of cancer. Further studies are warranted to explore the broader implications of this approach in clinical settings.

Keywords: natural killer (NK) cells, Cytotoxicity, Leukoreduction filter, IL-12 and IL-15 Cytokines

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3172 An Efficient Separation for Convolutive Mixtures

Authors: Salah Al-Din I. Badran, Samad Ahmadi, Dylan Menzies, Ismail Shahin

Abstract:

This paper describes a new efficient blind source separation method; in this method we use a non-uniform filter bank and a new structure with different sub-bands. This method provides a reduced permutation and increased convergence speed comparing to the full-band algorithm. Recently, some structures have been suggested to deal with two problems: reducing permutation and increasing the speed of convergence of the adaptive algorithm for correlated input signals. The permutation problem is avoided with the use of adaptive filters of orders less than the full-band adaptive filter, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full-band, and can promote better rates of convergence.

Keywords: Blind source separation, estimates, full-band, mixtures, sub-band

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3171 Development of Materials Based on Phosphates of NaZr2(PO4)3 with Low Thermal Expansion

Authors: V. Yu. Volgutov, A. I. Orlova, S. A. Khainakov

Abstract:

NaZr2(PO4)3 (NZP) and their structural analogues are characterized by a peculiar behaviors on heating – they have different expansion and contraction along different crystallographic directions due to specific arrangements of crystal structure in these compounds. An important feature of such structures is the ability to incorporate into their structural analogues wide variety of metal cations having different size and oxidation states, with different combinations and concentrations. These cations are located in different crystallographic non-equivalent positions of octahedral tetrahedral crystal framework as well as in inter-framework cavities. Through, due to iso- and hetero-valent isomorphism of the cations (and the anions) in NZP, it becomes possible to tuning the compositions and to obtain the compounds with ‘on a plan’ properties. For the design of compounds with low and ultra-low thermal expansion including those with tailored thermal expansion properties, the following crystallochemical principles it seems are promising: 1) Insertion into crystal M1 position the cations having different sizes and, 2) the variation in the composition of compounds, providing different occupation of crystal M1 position. Following these principles we have designed and synthesized the next NZP-type phosphates series: a) where radii of the cations in the M1 crystal position was varied: Zr1/4Zr2(PO4)3 - Th1/4Zr2(PO4)3 (series I); R1/3Zr2(PO4)3 where R= Nd, Eu, Er (series II), b) where the occupation of M1 crystal position was varied: Zr1/4Zr2(PO4)3-Er1/3Zr2(PO4)3 (series III) and Zr1/4Zr2(PO4)3-Sr1/2Zr2(PO4)3 (series IV). The thermal expansion parameters were determined over the range of 25-800ºC. For each series the minimum axial coefficient of thermal expansion αa = αb, αc and their anisotropy Δα = Iαa - αcI, 10-6 K-1 was found as next: -1.51, 1.07, 2.58 for Th1/4Zr2(PO4)3 (series I); -0.72, 0.10, 0.81 for Nd1/3Zr2(PO4)3 (series II); -2.78, 1.35, 4.12 for Er1/6Zr1/8Zr2(PO4)3 (series III); 2.23, 1.32, 0.91 for Sr1/2Zr2(PO4)3 (series IV). The measured tendencies of the thermal expansion of crystals were in good agreement with predicted ones. For one of the members from the studied phosphates namely Th1/16Zr3/16Zr2(PO4)3 structural refinement have been carried out at 25, 200, 600, and 800°C. The dependencies of the structural parameters with the temperature have been determined.

Keywords: high-temperature crystallography, NaZr2(PO4)3, (NZP) analogs, structural-chemical principles, tuning thermal expansion

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3170 Noise Removal Techniques in Medical Images

Authors: Amhimmid Mohammed Saffour, Abdelkader Salama

Abstract:

Filtering is a part of image enhancement techniques, it is used to enhance certain details such as edges in the image that are relevant to the application. Additionally, filtering can even be used to eliminate unwanted components of noise. Medical images typically contain salt and pepper noise and Poisson noise. This noise appears to the presence of minute grey scale variations within the image. In this paper, different filters techniques namely (Median, Wiener, Rank order3, Rank order5, and Average) were applied on CT medical images (Brain and chest). We using all these filters to remove salt and pepper noise from these images. This type of noise consists of random pixels being set to black or white. Peak Signal to Noise Ratio (PSNR), Mean Square Error r(MSE) and Histogram were used to evaluated the quality of filtered images. The results, which we have achieved shows that, these filters, are more useful and they prove to be helpful for general medical practitioners to analyze the symptoms of the patients with no difficulty.

Keywords: CT imaging, median filter, adaptive filter and average filter, MATLAB

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3169 Adaptive Neuro Fuzzy Inference System Model Based on Support Vector Regression for Stock Time Series Forecasting

Authors: Anita Setianingrum, Oki S. Jaya, Zuherman Rustam

Abstract:

Forecasting stock price is a challenging task due to the complex time series of the data. The complexity arises from many variables that affect the stock market. Many time series models have been proposed before, but those previous models still have some problems: 1) put the subjectivity of choosing the technical indicators, and 2) rely upon some assumptions about the variables, so it is limited to be applied to all datasets. Therefore, this paper studied a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) time series model based on Support Vector Regression (SVR) for forecasting the stock market. In order to evaluate the performance of proposed models, stock market transaction data of TAIEX and HIS from January to December 2015 is collected as experimental datasets. As a result, the method has outperformed its counterparts in terms of accuracy.

Keywords: ANFIS, fuzzy time series, stock forecasting, SVR

Procedia PDF Downloads 214
3168 Ultra-Tightly Coupled GNSS/INS Based on High Degree Cubature Kalman Filtering

Authors: Hamza Benzerrouk, Alexander Nebylov

Abstract:

In classical GNSS/INS integration designs, the loosely coupled approach uses the GNSS derived position and the velocity as the measurements vector. This design is suboptimal from the standpoint of preventing GNSSoutliers/outages. The tightly coupled GPS/INS navigation filter mixes the GNSS pseudo range and inertial measurements and obtains the vehicle navigation state as the final navigation solution. The ultra‐tightly coupled GNSS/INS design combines the I (inphase) and Q(quadrature) accumulator outputs in the GNSS receiver signal tracking loops and the INS navigation filter function intoa single Kalman filter variant (EKF, UKF, SPKF, CKF and HCKF). As mentioned, EKF and UKF are the most used nonlinear filters in the literature and are well adapted to inertial navigation state estimation when integrated with GNSS signal outputs. In this paper, it is proposed to move a step forward with more accurate filters and modern approaches called Cubature and High Degree cubature Kalman Filtering methods, on the basis of previous results solving the state estimation based on INS/GNSS integration, Cubature Kalman Filter (CKF) and High Degree Cubature Kalman Filter with (HCKF) are the references for the recent developed generalized Cubature rule based Kalman Filter (GCKF). High degree cubature rules are the kernel of the new solution for more accurate estimation with less computational complexity compared with the Gauss-Hermite Quadrature (GHQKF). Gauss-Hermite Kalman Filter GHKF which is not selected in this work because of its limited real-time implementation in high-dimensional state-spaces. In ultra tightly or a deeply coupled GNSS/INS system is dynamics EKF is used with transition matrix factorization together with GNSS block processing which is well described in the paper and assumes available the intermediary frequency IF by using a correlator samples with a rate of 500 Hz in the presented approach. GNSS (GPS+GLONASS) measurements are assumed available and modern SPKF with Cubature Kalman Filter (CKF) are compared with new versions of CKF called high order CKF based on Spherical-radial cubature rules developed at the fifth order in this work. Estimation accuracy of the high degree CKF is supposed to be comparative to GHKF, results of state estimation are then observed and discussed for different initialization parameters. Results show more accurate navigation state estimation and more robust GNSS receiver when Ultra Tightly Coupled approach applied based on High Degree Cubature Kalman Filter.

Keywords: GNSS, INS, Kalman filtering, ultra tight integration

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3167 Impact of Applying Bag House Filter Technology in Cement Industry on Ambient Air Quality - Case Study: Alexandria Cement Company

Authors: Haggag H. Mohamed, Ghatass F. Zekry, Shalaby A. Elsayed

Abstract:

Most sources of air pollution in Egypt are of anthropogenic origin. Alexandria Governorate is located at north of Egypt. The main contributing sectors of air pollution in Alexandria are industry, transportation and area source due to human activities. Alexandria includes more than 40% of the industrial activities in Egypt. Cement manufacture contributes a significant amount to the particulate pollution load. Alexandria Portland Cement Company (APCC) surrounding was selected to be the study area. APCC main kiln stack Total Suspended Particulate (TSP) continuous monitoring data was collected for assessment of dust emission control technology. Electro Static Precipitator (ESP) was fixed on the cement kiln since 2002. The collected data of TSP for first quarter of 2012 was compared to that one in first quarter of 2013 after installation of new bag house filter. In the present study, based on these monitoring data and metrological data a detailed air dispersion modeling investigation was carried out using the Industrial Source Complex Short Term model (ISC3-ST) to find out the impact of applying new bag house filter control technology on the neighborhood ambient air quality. The model results show a drastic reduction of the ambient TSP hourly average concentration from 44.94μg/m3 to 5.78μg/m3 which assures the huge positive impact on the ambient air quality by applying bag house filter technology on APCC cement kiln

Keywords: air pollution modeling, ambient air quality, baghouse filter, cement industry

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3166 Comparisons of Individual and Group Replacement Policies for a Series Connection System with Two Machines

Authors: Wen Liang Chang, Mei Wei Wang, Ruey Huei Yeh

Abstract:

This paper studies the comparisons of individual and group replacement policies for a series connection system with two machines. Suppose that manufacturer’s production system is a series connection system which is combined by two machines. For two machines, when machines fail within the operating time, minimal repair is performed for machines by the manufacturer. The manufacturer plans to a preventive replacement for machines at a pre-specified time to maintain system normal operation. Under these maintenance policies, the maintenance cost rate models of individual and group replacement for a series connection system with two machines is derived and further, optimal preventive replacement time is obtained such that the expected total maintenance cost rate is minimized. Finally, some numerical examples are given to illustrate the influences of individual and group replacement policies to the maintenance cost rate.

Keywords: individual replacement, group replacement, replacement time, two machines, series connection system

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3165 Notched Bands in Ultra-Wideband UWB Filter Design for Advanced Wireless Applications

Authors: Abdul Basit, Amil Daraz, Guoqiang Zhang

Abstract:

With the increasing demand for wireless communication systems for unlicensed indoor applications, the FCC, in February 2002, allocated unlicensed bands ranging from 3.1 GHZ to 10.6 GHz with fractional bandwidth of about 109 %, because it plays a key role in the radiofrequency (RF) front ends devices and has been widely applied in many other microwave circuits. Targeting the proposed band defined by the FCC for the UWB system, this article presents a UWB bandpass filter with three stop bands for the mitigation of wireless bands that may interfere with the UWB range. For this purpose, two resonators are utilized for the implementation of triple-notched bands. The C-shaped resonator is used for the first notch band creation at 3.4 GHz to suppress the WiMAX signal, while the H-shaped resonator is employed in the initial UWB design to introduce the dual notched characteristic at 4.5 GHz and 8.1 GHz to reject the WLAN and Satellite Communication signals. The overall circuit area covered by the proposed design is 30.6 mm × 20 mm, or in terms of guided wavelength at the first stopband, its size is 0.06 λg × 0.02 λg. The presented structure shows a good return loss under -10 dB over most of the passband and greater than -15 dB for the notched frequency bands. Finally, the filter is simulated and analyzed in HFSS 15.0. All the bands for the rejection of wireless signals are independently controlled, which makes this work superior to the rest of the UWB filters presented in the literature.

Keywords: a bandpass filter (BPF), ultra-wideband (UWB), wireless communication, C-shaped resonator, triple notch

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3164 State Estimation Method Based on Unscented Kalman Filter for Vehicle Nonlinear Dynamics

Authors: Wataru Nakamura, Tomoaki Hashimoto, Liang-Kuang Chen

Abstract:

This paper provides a state estimation method for automatic control systems of nonlinear vehicle dynamics. A nonlinear tire model is employed to represent the realistic behavior of a vehicle. In general, all the state variables of control systems are not precisedly known, because those variables are observed through output sensors and limited parts of them might be only measurable. Hence, automatic control systems must incorporate some type of state estimation. It is needed to establish a state estimation method for nonlinear vehicle dynamics with restricted measurable state variables. For this purpose, unscented Kalman filter method is applied in this study for estimating the state variables of nonlinear vehicle dynamics. The objective of this paper is to propose a state estimation method using unscented Kalman filter for nonlinear vehicle dynamics. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: state estimation, control systems, observer systems, nonlinear systems

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3163 Theory of the Optimum Signal Approximation Clarifying the Importance in the Recognition of Parallel World and Application to Secure Signal Communication with Feedback

Authors: Takuro Kida, Yuichi Kida

Abstract:

In this paper, it is shown a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detail algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output-signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory, and it is indicated that introducing conversations with feedback do not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: matrix filterbank, optimum signal approximation, category theory, simultaneous minimization

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3162 The Unscented Kalman Filter Implementation for the Sensorless Speed Control of a Permanent Magnet Synchronous Motor

Authors: Justas Dilys

Abstract:

ThispaperaddressestheimplementationandoptimizationofanUnscentedKalmanFilter(UKF) for the Permanent Magnet Synchronous Motor (PMSM) sensorless control using an ARM Cortex- M3 microcontroller. A various optimization levels based on arithmetic calculation reduction was implemented in ARM Cortex-M3 microcontroller. The execution time of UKF estimator was up to 90µs without loss of accuracy. Moreover, simulation studies on the Unscented Kalman filters are carried out using Matlab to explore the usability of the UKF in a sensorless PMSMdrive.

Keywords: unscented kalman filter, ARM, PMSM, implementation

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3161 Stock Price Prediction Using Time Series Algorithms

Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

Abstract:

This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

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3160 Signal Processing Approach to Study Multifractality and Singularity of Solar Wind Speed Time Series

Authors: Tushnik Sarkar, Mofazzal H. Khondekar, Subrata Banerjee

Abstract:

This paper investigates the nature of the fluctuation of the daily average Solar wind speed time series collected over a period of 2492 days, from 1st January, 1997 to 28th October, 2003. The degree of self-similarity and scalability of the Solar Wind Speed signal has been explored to characterise the signal fluctuation. Multi-fractal Detrended Fluctuation Analysis (MFDFA) method has been implemented on the signal which is under investigation to perform this task. Furthermore, the singularity spectra of the signals have been also obtained to gauge the extent of the multifractality of the time series signal.

Keywords: detrended fluctuation analysis, generalized hurst exponent, holder exponents, multifractal exponent, multifractal spectrum, singularity spectrum, time series analysis

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3159 Recursive Doubly Complementary Filter Design Using Particle Swarm Optimization

Authors: Ju-Hong Lee, Ding-Chen Chung

Abstract:

This paper deals with the optimal design of recursive doubly complementary (DC) digital filter design using a metaheuristic based optimization technique. Based on the theory of DC digital filters using two recursive digital all-pass filters (DAFs), the design problem is appropriately formulated to result in an objective function which is a weighted sum of the phase response errors of the designed DAFs. To deal with the stability of the recursive DC filters during the design process, we can either impose some necessary constraints on the phases of the recursive DAFs. Through a frequency sampling and a weighted least squares approach, the optimization problem of the objective function can be solved by utilizing a population based stochastic optimization approach. The resulting DC digital filters can possess satisfactory frequency response. Simulation results are presented for illustration and comparison.

Keywords: doubly complementary, digital all-pass filter, weighted least squares algorithm, particle swarm optimization

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3158 Effect of Fabrication Errors on High Frequency Filter Circuits

Authors: Wesam Ali

Abstract:

This paper provides useful guidelines to the circuit designers on the magnitude of fabrication errors in multilayer millimeter-wave components that are acceptable and presents data not previously reported in the literature. A particularly significant error that was quantified was that of skew between conductors on different layers, where it was found that a skew angle of only 0.1° resulted in very significant changes in bandwidth and insertion loss. The work was supported by a detailed investigation on a 35GHz, multilayer edge-coupled band-pass filter, which was fabricated on alumina substrates using photoimageable thick film process.

Keywords: fabrication errors, multilayer, high frequency band, photoimagable technology

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3157 A Comparative Study of Substituted Li Ferrites Sintered by the Conventional and Microwave Sintering Technique

Authors: Ibetombi Soibam

Abstract:

Li-Zn-Ni ferrite having the compositional formula Li0.4-0.5xZn0.2NixFe2.4-0.5xO4 where x = 0.02 ≤ x ≤0.1 in steps of 0.02 was fabricated by the citrate precursor method. In this method, metal nitrates and citric acid was used to prepare the gel which exhibit self-propagating combustion behavior giving the required ferrite sample. The ferrite sample was given a pre-firing at 650°C in a programmable conventional furnace for 3 hours with a heating rate of 5°C/min. A series of the sample was finally given conventional sintering (CS) at 1040°C after the pre-firing process. Another series was given microwave sintering (MS) at 1040°C in a programmable microwave furnace which uses a single magnetron operating at 2.45 GHz frequency. X- ray diffraction pattern confirmed the spinel phase structure for both the series. The theoretical and experimental density was calculated. It was observed that densification increases with the increase in Ni concentration in both the series. However, samples sintered by microwave technique was found to be denser. The microstructure of the two series of the sample was examined using scanning electron microscopy (SEM). Dielectric properties have been investigated as a function of frequency and composition for both series of samples sintered by CS and MS technique. The variation of dielectric constant with frequency show dispersion for both the series. It was explained in terms of Koop’s two layer model. From the analysis of dielectric measurement, it was observed that the value of room temperature dielectric constant decreases with the increase in Ni concentration for both the series. The microwave sintered samples show a lower dielectric constant making microwave sintering suitable for high-frequency applications. The possible mechanisms contributing to all the above behavior is being discussed.

Keywords: citrate precursor, dielectric constant, ferrites, microwave sintering

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3156 Comparison of Loosely Coupled and Tightly Coupled INS/GNSS Architecture for Guided Rocket Navigation System

Authors: Rahmat Purwoko, Bambang Riyanto Trilaksono

Abstract:

This paper gives comparison of INS/GNSS architecture namely Loosely Coupled and Tightly Coupled using Hardware in the Loop Simulation in Guided Missile RKX-200 rocket model. INS/GNSS Tightly Coupled architecture requires pseudo-range, pseudo-range rate, and position and velocity of each satellite in constellation from GPS (Global Positioning System) measurement. The Loosely Coupled architecture use estimated position and velocity from GNSS receiver. INS/GNSS architecture also requires angular rate and specific force measurement from IMU (Inertial Measurement Unit). Loosely Coupled arhitecture designed using 15 states Kalman Filter and Tightly Coupled designed using 17 states Kalman Filter. Integration algorithm calculation using ECEF frame. Navigation System implemented Zedboard All Programmable SoC.

Keywords: kalman filter, loosely coupled, navigation system, tightly coupled

Procedia PDF Downloads 276
3155 State Estimation Based on Unscented Kalman Filter for Burgers’ Equation

Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

Controlling the flow of fluids is a challenging problem that arises in many fields. Burgers’ equation is a fundamental equation for several flow phenomena such as traffic, shock waves, and turbulence. The optimal feedback control method, so-called model predictive control, has been proposed for Burgers’ equation. However, the model predictive control method is inapplicable to systems whose all state variables are not exactly known. In practical point of view, it is unusual that all the state variables of systems are exactly known, because the state variables of systems are measured through output sensors and limited parts of them can be only available. In fact, it is usual that flow velocities of fluid systems cannot be measured for all spatial domains. Hence, any practical feedback controller for fluid systems must incorporate some type of state estimator. To apply the model predictive control to the fluid systems described by Burgers’ equation, it is needed to establish a state estimation method for Burgers’ equation with limited measurable state variables. To this purpose, we apply unscented Kalman filter for estimating the state variables of fluid systems described by Burgers’ equation. The objective of this study is to establish a state estimation method based on unscented Kalman filter for Burgers’ equation. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: observer systems, unscented Kalman filter, nonlinear systems, Burgers' equation

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3154 Detection and Tracking Approach Using an Automotive Radar to Increase Active Pedestrian Safety

Authors: Michael Heuer, Ayoub Al-Hamadi, Alexander Rain, Marc-Michael Meinecke

Abstract:

Vulnerable road users, e.g. pedestrians, have a high impact on fatal accident numbers. To reduce these statistics, car manufactures are intensively developing suitable safety systems. Hereby, fast and reliable environment recognition is a major challenge. In this paper we describe a tracking approach that is only based on a 24 GHz radar sensor. While common radar signal processing loses much information, we make use of a track-before-detect filter to incorporate raw measurements. It is explained how the Range-Doppler spectrum can help to indicated pedestrians and stabilize tracking even in occultation scenarios compared to sensors in series.

Keywords: radar, pedestrian detection, active safety, sensor

Procedia PDF Downloads 488