Search results for: change point estimation

Authors: Linyu Wang, Furui Huo, Jianhong Xiang

Abstract:

The Doppler shift generated by high-speed movement and multipath effects in the channel are the main reasons for the generation of a time-frequency doubly-selective (DS) channel. There is severe inter-carrier interference (ICI) in the DS channel. Channel estimation for an orthogonal frequency division multiplexing (OFDM) system over a DS channel is very difficult. The simultaneous orthogonal matching pursuit (SOMP) algorithm under distributed compressive sensing theory (DCS-SOMP) has been used in channel estimation for OFDM systems over DS channels. However, the reconstruction accuracy of the DCS-SOMP algorithm is not high enough in the low Signal-to-Noise Ratio (SNR) stage. To solve this problem, in this paper, we propose an improved DCS-SOMP algorithm based on the inner product difference comparison operation (DCS-DCSOMP). The reconstruction accuracy is improved by increasing the number of candidate indexes and designing the comparison conditions of inner product difference. We combine the DCS-DCSOMP algorithm with the basis expansion model (BEM) to reduce the complexity of channel estimation. Simulation results show the effectiveness of the proposed algorithm and its advantages over other algorithms.

Keywords: OFDM, doubly selective, channel estimation, compressed sensing

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Authors: Jawad Ahmad, Hee-Jun Kim

Abstract:

This paper describes the design of a voltage based maximum power point tracker (MPPT) for photovoltaic (PV) applications. Of the various MPPT methods, the voltage based method is considered to be the simplest and cost effective. The major disadvantage of this method is that the PV array is disconnected from the load for the sampling of its open circuit voltage, which inevitably results in power loss. Another disadvantage, in case of rapid irradiance variation, is that if the duration between two successive samplings, called the sampling period, is too long there is a considerable loss. This is because the output voltage of the PV array follows the unchanged reference during one sampling period. Once a maximum power point (MPP) is tracked and a change in irradiation occurs between two successive samplings, then the new MPP is not tracked until the next sampling of the PV array voltage. This paper proposes an MPPT circuit in which the sampling interval of the PV array voltage, and the sampling period have been shortened. The sample and hold circuit has also been simplified. The proposed circuit does not utilize a microcontroller or a digital signal processor and is thus suitable for low cost and low power applications.

Keywords: Maximum power point tracker, Sample and hold amplifier, Sampling interval, Sampling period.

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Authors: Reza Hayati, Maryam Sadi, Saeid Shokri, Mehdi Ahmadi Marvast, Saeid Hassan Boroojerdi, Amin Hamzavi Abedi

Abstract:

Efficient and safe plant operation can only be achieved if the operators are able to monitor all key process parameters. Instrumentation is used to measure many process variables, like temperatures, pressures, flow rates, compositions or other product properties. Therefore Performance monitoring is a suitable tool for operators. In this paper, we integrate rigorous simulation model, data reconciliation and parameter estimation to monitor process equipments and determine key performance indicator (KPI) of them. The applied method here has been implemented in two case studies.

Keywords: Data Reconciliation, Measurement, Optimization, Parameter Estimation, Performance Monitoring.

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Authors: Aly Farag, Ayman El-Baz, Refaat Mohamed

Abstract:

In this paper we present a novel approach for density estimation. The proposed approach is based on using the logistic regression model to get initial density estimation for the given empirical density. The empirical data does not exactly follow the logistic regression model, so, there will be a deviation between the empirical density and the density estimated using logistic regression model. This deviation may be positive and/or negative. In this paper we use a linear combination of Gaussian (LCG) with positive and negative components as a model for this deviation. Also, we will use the expectation maximization (EM) algorithm to estimate the parameters of LCG. Experiments on real images demonstrate the accuracy of our approach.

Keywords: Logistic regression model, Expectationmaximization, Segmentation.

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Authors: Yong-An Jung, Young-Hwan You

Abstract:

This paper suggests an improved integer frequency offset (IFO) estimation scheme using P1 symbol for orthogonal frequency division multiplexing (OFDM) based the second generation terrestrial digital video broadcasting (DVB-T2) system. Proposed IFO estimator is designed by a low-complexity blind IFO estimation scheme, which is implemented with complex additions. Also, we propose active carriers (ACs) selection scheme in order to prevent performance degradation in blind IFO estimation. The simulation results show that under the AWGN and TU6 channels, the proposed method has low complexity than conventional method and almost similar performance in comparison with the conventional method.

Keywords: OFDM, DVB-T2, P1 symbol, ACs, IFO.

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Authors: Beata Czarnacka-Chrobot

Abstract:

Majority of Business Software Systems (BSS) Development and Enhancement Projects (D&EP) fail to meet criteria of their effectiveness, what leads to the considerable financial losses. One of the fundamental reasons for such projects- exceptionally low success rate are improperly derived estimates for their costs and time. In the case of BSS D&EP these attributes are determined by the work effort, meanwhile reliable and objective effort estimation still appears to be a great challenge to the software engineering. Thus this paper is aimed at presenting the most important synthetic conclusions coming from the author-s own studies concerning the main factors of effective BSS D&EP work effort estimation. Thanks to the rational investment decisions made on the basis of reliable and objective criteria it is possible to reduce losses caused not only by abandoned projects but also by large scale of overrunning the time and costs of BSS D&EP execution.

Keywords: Benchmarking data, business software systems development and enhancement projects, effort estimation, software engineering economics, software functional size measurement.

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Authors: Tienfuan Kerh, Hsienchang Lu, Rob Saunders

Abstract:

Shoreline erosion problems caused by global warming and sea level rising may result in losing of land areas, so it should be examined regularly to reduce possible negative impacts. Initially in this study, three sets of survey images obtained from the years of 1990, 2001, and 2010, respectively, are digitalized by using graphical software to establish the spatial coordinates of six major beaches around the island of Taiwan. Then, by overlaying the known multi-period images, the change of shoreline can be observed from their distribution of coordinates. In addition, the neural network approximation is used to develop a model for predicting shoreline variation in the years of 2015 and 2020. The comparison results show that there is no significant change of total sandy area for all beaches in the three different periods. However, the prediction results show that two beaches may exhibit an increasing of total sandy areas under a statistical 95% confidence interval. The proposed method adopted in this study may be applicable to other shorelines of interest around the world.

Keywords: Digitalized shoreline coordinates, survey image overlaying, neural network approximation, total beach sandy areas.

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Authors: Keunhong Chae, Seokho Yoon

Abstract:

We address the integer frequency offset (IFO) estimation under the influence of the timing offset (TO) in orthogonal frequency division multiplexing (OFDM) systems. Incorporating the IFO and TO into the symbol set used to represent the received OFDM symbol, we investigate the influence of the TO on the IFO, and then, propose a combining method between two consecutive OFDM correlations, reducing the influence. The proposed scheme has almost the same complexity as that of the conventional schemes, whereas it does not need the TO knowledge contrary to the conventional schemes. From numerical results it is confirmed that the proposed scheme is insensitive to the TO, consequently, yielding an improvement of the IFO estimation performance over the conventional schemes when the TO exists.

Keywords: Estimation, integer frequency offset, OFDM, timing offset.

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Authors: Sambit Prasad Kar, P.Palanisamy

Abstract:

In this paper a novel method for multiple one dimensional real valued sinusoidal signal frequency estimation in the presence of additive Gaussian noise is postulated. A computationally simple frequency estimation method with efficient statistical performance is attractive in many array signal processing applications. The prime focus of this paper is to combine the subspace-based technique and a simple peak search approach. This paper presents a variant of the Propagator Method (PM), where a collaborative approach of SUMWE and Propagator method is applied in order to estimate the multiple real valued sine wave frequencies. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. The statistical analysis of the proposed method is studied, and the explicit expression of asymptotic (large-sample) mean-squared-error (MSE) or variance of the estimation error is derived. The performance of the method is demonstrated, and the theoretical analysis is substantiated through numerical examples. The proposed method can achieve sustainable high estimation accuracy and frequency resolution at a lower SNR, which is verified by simulation by comparing with conventional MUSIC, ESPRIT and Propagator Method.

Keywords: Frequency estimation, peak search, subspace-based method without eigen decomposition, quadratic convex function.

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Authors: Hasan.O. Farahneh, Ayman A. Issa

Abstract:

Software development is moving towards agility with use cases and scenarios being used for requirements stories. Estimates of software costs are becoming even more important than before as effects of delays is much larger in successive short releases context of agile development. Thus, this paper reports on the development of new linear use case based software cost estimation model applicable in the very early stages of software development being based on simple metric. Evaluation showed that accuracy of estimates varies between 43% and 55% of actual effort of historical test projects. These results outperformed those of wellknown models when applied in the same context. Further work is being carried out to improve the performance of the proposed model when considering the effect of non-functional requirements.

Keywords: Metrics, Software Cost Estimation, Use Cases

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Authors: Giulio Rosati, Luciano Sappia, Rossana Madrid, Noemi Rozlòsnik

Abstract:

The addition of PEG of different molecular weights has important effects on the physical, electrical and electrochemical properties of iron(III)-tosylate doped PEDOT. This particular polymer can be easily spin coated over plastic discs, optimizing thickness and uniformity of the PEDOT-PEG films. The conductivity and morphological analysis of the hybrid PEDOT-PEG polymer by 4-point probe (4PP), 12-point probe (12PP), and conductive AFM (C-AFM) show strong effects of the PEG doping. Moreover, the conductive films kinetics at the nanoscale, in response to different bias voltages, change radically depending on the PEG molecular weight. The hybrid conductive films show also interesting electrochemical properties, making the PEDOT PEG doping appealing for biosensing applications both for EIS-based and amperometric affinity/catalytic biosensors.

Keywords: Atomic force microscopy, biosensors, four-point probe, nano-films, PEDOT.

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Authors: K. Kouzi

Abstract:

In order to have stable and high performance of direct torque and flux control (DTFC) of double star induction motor drive (DSIM), proper on-line adaptation of the stator resistance is very important. This is inevitably due to the variation of the stator resistance during operating conditions, which introduces error in estimated flux position and the magnitude of the stator flux. Error in the estimated stator flux deteriorates the performance of the DTFC drive. Also, the effect of error in estimation is very important especially at low speed. Due to this, our aim is to overcome the sensitivity of the DTFC to the stator resistance variation by proposing on-line fuzzy estimation stator resistance. The fuzzy estimation method is based on an on-line stator resistance correction through the variations of the stator current estimation error and its variations. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of the suggested algorithm control is to avoid the drive instability that may occur in certain situations and ensure the tracking of the actual stator resistance. The validity of the technique and the improvement of the whole system performance are proved by the results.

Keywords: Direct torque control, dual stator induction motor, fuzzy logic estimation, stator resistance adaptation.

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Authors: Pakkinee Chitsakul

Abstract:

In this article, we would like to show that there is no cut point of any point in a plane, but there exists the cut locus of a point in a flat torus. By the results, we would like to determine the structure of cut locus of a flat torus.

Keywords: Cut locus, flat torus, geodesics.

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Authors: Jean-Pierre Dubois, Rania Minkara, Rafic Ayoubi

Abstract:

Maximal Ratio Combining (MRC) is considered the most complex combining technique as it requires channel coefficients estimation. It results in the lowest bit error rate (BER) compared to all other combining techniques. However the BER starts to deteriorate as errors are introduced in the channel coefficients estimation. A novel combining technique, termed Generalized Maximal Ratio Combining (GMRC) with a polynomial kernel, yields an identical BER as MRC with perfect channel estimation and a lower BER in the presence of channel estimation errors. We show that GMRC outperforms the optimal MRC scheme in general and we hereinafter introduce it to the scientific community as a new “supraoptimal" algorithm. Since diversity combining is especially effective in small femto- and pico-cells, internet-associated wireless peripheral systems are to benefit most from GMRC. As a result, many spinoff applications can be made to IP-based 4th generation networks.

Keywords: Bit error rate, femto-internet cells, generalized maximal ratio combining, signal-to-scattering noise ratio.

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Authors: D. Karthikeyan, G. Balakrishnan

Abstract:

Human faces, as important visual signals, express a significant amount of nonverbal info for usage in human-to-human communication. Age, specifically, is more significant among these properties. Human age estimation using facial image analysis as an automated method which has numerous potential real‐world applications. In this paper, an automated age estimation framework is presented. Support Vector Regression (SVR) strategy is utilized to investigate age prediction. This paper depicts a feature extraction taking into account Gray Level Co-occurrence Matrix (GLCM), which can be utilized for robust face recognition framework. It applies GLCM operation to remove the face's features images and Active Appearance Models (AAMs) to assess the human age based on image. A fused feature technique and SVR with GA optimization are proposed to lessen the error in age estimation.

Keywords: Support vector regression, feature extraction, gray level co-occurrence matrix, active appearance models.

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Authors: H. A. Rahim, U. U. Sheikh, R. B. Ahmad, A. S. M. Zain

Abstract:

This paper describes an algorithm to estimate realtime vehicle velocity using image processing technique from the known camera calibration parameters. The presented algorithm involves several main steps. First, the moving object is extracted by utilizing frame differencing technique. Second, the object tracking method is applied and the speed is estimated based on the displacement of the object-s centroid. Several assumptions are listed to simplify the transformation of 2D images from 3D real-world images. The results obtained from the experiment have been compared to the estimated ground truth. From this experiment, it exhibits that the proposed algorithm has achieved the velocity accuracy estimation of about ± 1.7 km/h.

Keywords: camera calibration, object tracking, velocity estimation, video image processing

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Authors: N. R. P Withana, E. Auch

Abstract:

The purpose of this study was to investigate perceptions of climate change risk to forest ecosystems and forestbased communities as well as perceived effectiveness of adaptation strategies for climate change as well as challenges for adaptation. Data was gathered using a pre-tested semi-structured questionnaire. Simple random selection technique was applied. For the majority of issues, the responses were obtained on multi-point likert scales, and the scores provided were, in turn, used to estimate the means and other useful estimates. A composite knowledge index developed using correct responses to a set of self-rated statements were used to evaluate the issues. The mean of the knowledge index was 0.64. Also all respondents recorded values of the knowledge index above 0.25. Increase forest fire was perceived by respondents as the greatest risk to forest eco-system. Decrease access to water supplies was perceived as the greatest risk to livelihoods of forest based communities. The most effective adaptation strategy relevant to climate change risks to forest eco-systems and forest based communities livelihoods in Kathmandu valley in Nepal as perceived by the respondents was reforestation and afforestation. As well, lack of public awareness was perceived as the major limitation for climate change adaptation. However, perceived risks as well as effective adaptation strategies showed an inconsistent association with knowledge indicators and social-cultural variables. The results provide useful information to any party who involve with climate change issues in Nepal, since such attempts would be more effective once the people’s perceptions on these aspects are taken into account.

Keywords: Climate change, forest ecosystems, forest-based communities, risk perceptions.

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Authors: Gouri Prakash

Abstract:

One of the common problems encountered in software engineering is addressing and responding to the changing nature of requirements. While several approaches have been devised to address this issue, ranging from instilling resistance to changing requirements in order to mitigate impact to project schedules, to developing an agile mindset towards requirements, the approach discussed in this paper is one of conceptualizing the delta in requirement and modeling it, in order to plan a response to it. To provide some context here, change is first formally identified and categorized as either formal change or informal change. While agile methodology facilitates informal change, the approach discussed in this paper seeks to develop the idea of facilitating formal change. To collect, document meta-requirements that represent the phenomena of change would be a pro-active measure towards building a realistic cognition of the requirements entity that can further be harnessed in the software engineering process.

Keywords: Change Management, Agile methodology, Metarequirements

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Authors: Wael M. El-Mamlouk, Metwally A. El-Sharkawy, Hossam. E. Mostafa

Abstract:

In this paper, we analyze and test a scheme for the estimation of electrical fundamental frequency signals from the harmonic load current and voltage signals. The scheme was based on using two different Multi Layer Artificial Neural Networks (ML-ANN) one for the current and the other for the voltage. This study also analyzes and tests the effect of choosing the optimum artificial neural networks- sizes which determine the quality and accuracy of the estimation of electrical fundamental frequency signals. The simulink tool box of the Matlab program for the simulation of the test system and the test of the neural networks has been used.

Keywords: Harmonics, Neural Networks, Modeling, Simulation, Active filters, electric Networks.

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Authors: Monika Garg, Lillie Dewan

Abstract:

Three novel and significant contributions are made in this paper Firstly, non-recursive formulation of Haar connection coefficients, pioneered by the present authors is presented, which can be computed very efficiently and avoid stack and memory overflows. Secondly, the generalized approach for state analysis of singular bilinear time-invariant (TI) and time-varying (TV) systems is presented; vis-˜a-vis diversified and complex works reported by different authors. Thirdly, a generalized approach for parameter estimation of bilinear TI and TV systems is also proposed. The unified framework of the proposed method is very significant in that the digital hardware once-designed can be used to perform the complex tasks of state analysis and parameter estimation of different types of bilinear systems single-handedly. The simplicity, effectiveness and generalized nature of the proposed method is established by applying it to different types of bilinear systems for the two tasks.

Keywords: Bilinear Systems, Haar Wavelet, Haar ConnectionCoefficients, Parameter Estimation, Singular Bilinear Systems, StateAnalysis.

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Authors: Seyed-Yaser Nabavi-Chashmi, Davood Asadi, Karim Ahmadi, Eren Demir

Abstract:

The landing phase of a UAV is very critical as there are many uncertainties in this phase, which can easily entail a hard landing or even a crash. In this paper, the estimation of relative distance and velocity to the ground, as one of the most important processes during the landing phase, is studied. Using accurate measurement sensors as an alternative approach can be very expensive for sensors like LIDAR, or with a limited operational range, for sensors like ultrasonic sensors. Additionally, absolute positioning systems like GPS or IMU cannot provide distance to the ground independently. The focus of this paper is to determine whether we can measure the relative distance and velocity of UAV and ground in the landing phase using just low-resolution images taken by a monocular camera. The Lucas-Konda feature detection technique is employed to extract the most suitable feature in a series of images taken during the UAV landing. Two different approaches based on Extended Kalman Filters (EKF) have been proposed, and their performance in estimation of the relative distance and velocity are compared. The first approach uses the kinematics of the UAV as the process and the calculated optical flow as the measurement. On the other hand, the second approach uses the feature’s projection on the camera plane (pixel position) as the measurement while employing both the kinematics of the UAV and the dynamics of variation of projected point as the process to estimate both relative distance and relative velocity. To verify the results, a sequence of low-quality images taken by a camera that is moving on a specifically developed testbed has been used to compare the performance of the proposed algorithm. The case studies show that the quality of images results in considerable noise, which reduces the performance of the first approach. On the other hand, using the projected feature position is much less sensitive to the noise and estimates the distance and velocity with relatively high accuracy. This approach also can be used to predict the future projected feature position, which can drastically decrease the computational workload, as an important criterion for real-time applications.

Keywords: Automatic landing, multirotor, nonlinear control, parameters estimation, optical flow.

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Authors: Manoj Parmar

Abstract:

The article uses reflexivity as a research method to investigate and propose an architectural theory plan for climate change. It hypothecates that to discuss or formulate discourse on "architectural paradigm and climate change," firstly, we need to understand the modes of integration that enable architectural thinking with climate change. The research intends to study the various integration modes that have evolved historically and situate them in time. Subsequently, it analyzes the integration pattern, challenges the existing model, and finds a way towards climate change as central to architectural thinking. The study is fundamental on-premises that ecology and climate change scholarship has consistently out lashed the asymmetrical and nonlinear knowledge and needs approaches for architecture that are less burden to climate change to people and minimize its impact on ecology.

Keywords: Climate change, architectural theory, reflexivity, modernity.

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Authors: M. R. Yadav, A. K. Sharma, B. S. Thakur

Abstract:

The purpose of this paper is to present a best proximity point theorems through rational expression for a combination of contraction condition, Kannan and Chatterjea nonlinear cyclic contraction in what we call MT-K and MT-C rational cyclic contraction. Some best proximity point theorems for a mapping satisfy these conditions have been established in metric spaces. We also give some examples to support our work.

Keywords: Cyclic contraction, rational cyclic contraction, best proximity point and complete metric space.

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Authors: H. Nemmour, Y. Chibani

Abstract:

Decision fusion is one of hot research topics in classification area, which aims to achieve the best possible performance for the task at hand. In this paper, we investigate the usefulness of this concept to improve change detection accuracy in remote sensing. Thereby, outputs of two fuzzy change detectors based respectively on simultaneous and comparative analysis of multitemporal data are fused by using fuzzy integral operators. This method fuses the objective evidences produced by the change detectors with respect to fuzzy measures that express the difference of performance between them. The proposed fusion framework is evaluated in comparison with some ordinary fuzzy aggregation operators. Experiments carried out on two SPOT images showed that the fuzzy integral was the best performing. It improves the change detection accuracy while attempting to equalize the accuracy rate in both change and no change classes.

Keywords: change detection, decision fusion, fuzzy logic, remote sensing.

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Authors: Yoshifumi Sakamoto, Kouichi Ono, Takeo Nakada, Yousuke Kubo, Hiroto Yasuura

Abstract:

This paper describes a system-level SoC energy consumption estimation method based on a dynamic behavior of embedded software in the early stages of the SoC development. A major problem of SOC development is development rework caused by unreliable energy consumption estimation at the early stages. The energy consumption of an SoC used in embedded systems is strongly affected by the dynamic behavior of the software. At the early stages of SoC development, modeling with a high level of abstraction is required for both the dynamic behavior of the software, and the behavior of the SoC. We estimate the energy consumption by a UML model-based simulation. The proposed method is applied for an actual embedded system in an MFP. The energy consumption estimation of the SoC is more accurate than conventional methods and this proposed method is promising to reduce the chance of development rework in the SoC development. ∈

Keywords: SoC, Embedded Sytem, Energy Consumption, Dynamic behavior, UML, Modeling, Model-based simulation

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Authors: Gaurav Kumar, Dharmbir Prasad, Rudra Pratap Singh

Abstract:

In the current work, adaptive extended Kalman filter (AEKF) is presented for solution of ground radar based ballistic missile (BM) tracking problem in re-entry phase with unknown ballistic coefficient. The estimation of trajectory of any BM in re-entry phase is extremely difficult, because of highly non-linear motion of BM. The estimation accuracy of AEKF has been tested for a typical test target tracking problem adopted from literature. Further, the approach of AEKF is compared with extended Kalman filter (EKF). The simulation result indicates the superiority of the AEKF in solving joint parameter and state estimation problems.

Keywords: Adaptive, AEKF, ballistic missile, EKF, re-entry phase, target tracking.

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Authors: C. Ganesh Babu, P. T. Vanathi

Abstract:

In this paper we present an enhanced noise reduction method for robust speech recognition using Adaptive Gain Equalizer with Non linear Spectral Subtraction. In Adaptive Gain Equalizer method (AGE), the input signal is divided into a number of subbands that are individually weighed in time domain, in accordance to the short time Signal-to-Noise Ratio (SNR) in each subband estimation at every time instant. Instead of focusing on suppression the noise on speech enhancement is focused. When analysis was done under various noise conditions for speech recognition, it was found that Adaptive Gain Equalizer method algorithm has an obvious failing point for a SNR of -5 dB, with inadequate levels of noise suppression for SNR less than this point. This work proposes the implementation of AGE when coupled with Non linear Spectral Subtraction (AGE-NSS) for robust speech recognition. The experimental result shows that out AGE-NSS performs the AGE when SNR drops below -5db level.

Keywords: Adaptive Gain Equalizer, Non Linear Spectral Subtraction, Speech Enhancement, and Speech Recognition.

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Authors: Xiaochuan Chen, Jianguo Yang, Beizhi Li

Abstract:

Design for cost (DFC) is a method that reduces life cycle cost (LCC) from the angle of designers. Multiple domain features mapping (MDFM) methodology was given in DFC. Using MDFM, we can use design features to estimate the LCC. From the angle of DFC, the design features of family cars were obtained, such as all dimensions, engine power and emission volume. At the conceptual design stage, cars- LCC were estimated using back propagation (BP) artificial neural networks (ANN) method and case-based reasoning (CBR). Hamming space was used to measure the similarity among cases in CBR method. Levenberg-Marquardt (LM) algorithm and genetic algorithm (GA) were used in ANN. The differences of LCC estimation model between CBR and artificial neural networks (ANN) were provided. ANN and CBR separately each method has its shortcomings. By combining ANN and CBR improved results accuracy was obtained. Firstly, using ANN selected some design features that affect LCC. Then using LCC estimation results of ANN could raise the accuracy of LCC estimation in CBR method. Thirdly, using ANN estimate LCC errors and correct errors in CBR-s estimation results if the accuracy is not enough accurate. Finally, economically family cars and sport utility vehicle (SUV) was given as LCC estimation cases using this hybrid approach combining ANN and CBR.

Keywords: case-based reasoning, life cycle cost (LCC), artificialneural networks (ANN), family cars

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Authors: Heung Jae Cho, Jae Il Park

Abstract:

This paper presents the development of an MODAPTS based cost estimating system to help designers in estimating the manufacturing cost of a assembly products which is belonged from the workers in working fields. Competitiveness of manufacturing cost is getting harder because of the development of Information and telecommunication, but also globalization. Therefore, the accuracy of the assembly cost estimation is getting important. DFA and MODAPTS is useful method for measuring the working hour. But these two methods are used just as a timetable. Therefore, in this paper, we suggest the process of measuring the working hours by MODAPTS which includes the working field-s accurate information. In addition, we adduce the estimation method of accuracy assembly cost with the real information. This research could be useful for designers that can estimate the assembly cost more accurately, and also effective for the companies that which are concerned to reduce the product cost.

Keywords: Cost estimation, DFA, MODAPTS, Assembly cost

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Authors: Lili Wang

Abstract:

By using the estimation of the Cauchy matrix of linear impulsive differential equations and Banach fixed point theorem as well as Gronwall-Bellman’s inequality, some sufficient conditions are obtained for the existence and exponential stability of almost periodic solution for an impulsive neural networks with distributed delays. An example is presented to illustrate the feasibility and  effectiveness of the results.

Keywords: Almost periodic solution, Exponential stability, Neural networks, Impulses.

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