Search results for: Noise Disturbance
229 Neural Network Ensemble-based Solar Power Generation Short-Term Forecasting
Authors: A. Chaouachi, R.M. Kamel, R. Ichikawa, H. Hayashi, K. Nagasaka
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This paper presents the applicability of artificial neural networks for 24 hour ahead solar power generation forecasting of a 20 kW photovoltaic system, the developed forecasting is suitable for a reliable Microgrid energy management. In total four neural networks were proposed, namely: multi-layred perceptron, radial basis function, recurrent and a neural network ensemble consisting in ensemble of bagged networks. Forecasting reliability of the proposed neural networks was carried out in terms forecasting error performance basing on statistical and graphical methods. The experimental results showed that all the proposed networks achieved an acceptable forecasting accuracy. In term of comparison the neural network ensemble gives the highest precision forecasting comparing to the conventional networks. In fact, each network of the ensemble over-fits to some extent and leads to a diversity which enhances the noise tolerance and the forecasting generalization performance comparing to the conventional networks.Keywords: Neural network ensemble, Solar power generation, 24 hour forecasting, Comparative study
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3276228 Efficient Detection Using Sequential Probability Ratio Test in Mobile Cognitive Radio Systems
Authors: Yeon-Jea Cho, Sang-Uk Park, Won-Chul Choi, Dong-Jo Park
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This paper proposes a smart design strategy for a sequential detector to reliably detect the primary user-s signal, especially in fast fading environments. We study the computation of the log-likelihood ratio for coping with a fast changing received signal and noise sample variances, which are considered random variables. First, we analyze the detectability of the conventional generalized log-likelihood ratio (GLLR) scheme when considering fast changing statistics of unknown parameters caused by fast fading effects. Secondly, we propose an efficient sensing algorithm for performing the sequential probability ratio test in a robust and efficient manner when the channel statistics are unknown. Finally, the proposed scheme is compared to the conventional method with simulation results with respect to the average number of samples required to reach a detection decision.
Keywords: Cognitive radio, fast fading, sequential detection, spectrum sensing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1743227 Sparse Coding Based Classification of Electrocardiography Signals Using Data-Driven Complete Dictionary Learning
Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul
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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.Keywords: Electrocardiogram, dictionary learning, sparse coding, classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2093226 A Soft Switching PWM DC-DC Boost Converter with Increased Efficiency by Using ZVT-ZCT Techniques
Authors: Yakup Sahin, Naim Suleyman Ting, Ismail Aksoy
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In this paper, an improved active snubber cell is proposed on account of soft switching (SS) family of pulse width modulation (PWM) DC-DC converters. The improved snubber cell provides zero-voltage transition (ZVT) turn on and zero-current transition (ZCT) turn off for main switch. The snubber cell decreases EMI noise and operates with SS in a wide range of line and load voltages. Besides, all of the semiconductor devices in the converter operate with SS. There is no additional voltage and current stress on the main devices. Additionally, extra voltage stress does not occur on the auxiliary switch and its current stress is acceptable value. The improved converter has a low cost and simple structure. The theoretical analysis of converter is clarified and the operating states are given in detail. The experimental results of converter are obtained by prototype of 500 W and 100 kHz. It is observed that the experimental results and theoretical analysis of converter are suitable with each other perfectly.Keywords: Active snubber cells, DC-DC converters, zero-voltage transition, zero-current transition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1929225 Video Super-Resolution Using Classification ANN
Authors: Ming-Hui Cheng, Jyh-Horng Jeng
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In this study, a classification-based video super-resolution method using artificial neural network (ANN) is proposed to enhance low-resolution (LR) to high-resolution (HR) frames. The proposed method consists of four main steps: classification, motion-trace volume collection, temporal adjustment, and ANN prediction. A classifier is designed based on the edge properties of a pixel in the LR frame to identify the spatial information. To exploit the spatio-temporal information, a motion-trace volume is collected using motion estimation, which can eliminate unfathomable object motion in the LR frames. In addition, temporal lateral process is employed for volume adjustment to reduce unnecessary temporal features. Finally, ANN is applied to each class to learn the complicated spatio-temporal relationship between LR and HR frames. Simulation results show that the proposed method successfully improves both peak signal-to-noise ratio and perceptual quality.
Keywords: Super-resolution, classification, spatio-temporal information, artificial neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1805224 Blind Identification Channel Using Higher Order Cumulants with Application to Equalization for MC−CDMA System
Authors: Mohammed Zidane, Said Safi, Mohamed Sabri, Ahmed Boumezzough
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In this paper we propose an algorithm based on higher order cumulants, for blind impulse response identification of frequency radio channels and downlink (MC−CDMA) system Equalization. In order to test its efficiency, we have compared with another algorithm proposed in the literature, for that we considered on theoretical channel as the Proakis’s ‘B’ channel and practical frequency selective fading channel, called Broadband Radio Access Network (BRAN C), normalized for (MC−CDMA) systems, excited by non-Gaussian sequences. In the part of (MC−CDMA), we use the Minimum Mean Square Error (MMSE) equalizer after the channel identification to correct the channel’s distortion. The simulation results, in noisy environment and for different signal to noise ratio (SNR), are presented to illustrate the accuracy of the proposed algorithm.
Keywords: Blind identification and equalization, Higher Order Cumulants, (MC−CDMA) system, MMSE equalizer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1781223 A Novel NIRS Index to Evaluate Brain Activity in Prefrontal Regions While Listening to First and Second Languages for Long Time Periods
Authors: Kensho Takahashi, Ko Watanabe, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara
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Near-infrared spectroscopy (NIRS) has been widely used as a non-invasive method to measure brain activity, but it is corrupted by baseline drift noise. Here we present a method to measure regional cerebral blood flow as a derivative of NIRS output. We investigate whether, when listening to languages, blood flow can reasonably localize and represent regional brain activity or not. The prefrontal blood flow distribution pattern when advanced second-language listeners listened to a second language (L2) was most similar to that when listening to their first language (L1) among the patterns of mean and standard deviation. In experiments with 25 healthy subjects, the maximum blood flow was localized to the left BA46 of advanced listeners. The blood flow presented is robust to baseline drift and stably localizes regional brain activity.
Keywords: NIRS, oxy-hemoglobin, baseline drift, blood flow, working memory, BA46, first language, second language.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2277222 Mitigation of ISI for Next Generation Wireless Channels in Outdoor Vehicular Environments
Authors: Mohd. Israil, M. Salim Beg
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In order to accommodate various multimedia services, next generation wireless networks are characterized by very high transmission bit rates. Thus, in such systems and networks, the received signal is not only limited by noise but - especially with increasing symbols rate often more significantly by the intersymbol interference (ISI) caused by the time dispersive radio channels such as those are used in this work. This paper deals with the study of the performance of detector for high bit rate transmission on some worst case models of frequency selective fading channels for outdoor mobile radio environments. This paper deals with a number of different wireless channels with different power profiles and different number of resolvable paths. All the radio channels generated in this paper are for outdoor vehicular environments with Doppler spread of 100 Hz. A carrier frequency of 1800 MHz is used and all the channels used in this work are such that they are useful for next generation wireless systems. Schemes for mitigation of ISI with adaptive equalizers of different types have been investigated and their performances have been investigated in terms of BER measured as a function of SNR.Keywords: Mobile channels, Rayleigh Fading, Equalization, NMLD.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1421221 Influence of Inertial Forces of Large Bearings Utilized in Wind Energy Assemblies
Authors: S. Barabas, F. Sarbu, B. Barabas, A. Fota
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Main objective of this paper is to establish a link between inertial forces of the bearings used in construction of wind power plant and its behavior. Using bearings with lower inertial forces has the immediate effect of decreasing inertia rotor system, with significant results in increased energy efficiency, due to decreased friction forces between rollers and raceways. The F.E.M. analysis shows the appearance of uniform contact stress at the ends of the rollers, demonstrated the necessity of production of low mass bearings. Favorable results are expected in the economic field, by reducing material consumption and by increasing the durability of bearings. Using low mass bearings with hollow rollers instead of solid rollers has an impact on working temperature, on vibrations and noise which decrease. Implementation of types of hollow rollers of cylindrical tubular type, instead of expensive rollers with logarithmic profile, will bring significant inertial forces decrease with large benefits in behavior of wind power plant.Keywords: Inertial forces, Von Mises stress, hollow rollers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2267220 A Double Differential Chaos Shift Keying Scheme for Ultra-Wideband Chaotic Communication Technology Applied in Low-Rate Wireless Personal Area Network
Authors: Ghobad Gorji, Hasan Golabi
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The goal of this paper is to describe the design of an ultra-wideband (UWB) system that is optimized for the low-rate wireless personal area network application. To this aim, we propose a system based on direct chaotic communication (DCC) technology. Based on this system, a 2-GHz wide chaotic signal is produced into the UWB spectrum lower band, i.e., 3.1–5.1 GHz. For this system, two simple modulation schemes, namely chaotic on-off keying (COOK) and differential chaos shift keying (DCSK) are evaluated first. We propose a modulation scheme, namely Double DCSK, to improve the performance of UWB DCC. Different characteristics of these systems, with Monte Carlo simulations based on the Additive White Gaussian Noise (AWGN) and the IEEE 802.15.4a standard channel models, are compared.
Keywords: Ultra-wideband, UWB, Direct Chaotic Communication, DCC, IEEE 802.15.4a, COOK, DCSK.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 209219 Developing an Advanced Algorithm Capable of Classifying News, Articles and Other Textual Documents Using Text Mining Techniques
Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas
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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.
Keywords: Artificial neural network, competitive dynamics, logistic regression, text classification, text mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 535218 Vibration, Lubrication and Machinery Consideration for a Mixer Gearbox Related to Iran Oil Industries
Authors: Omid A. Zargar
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In this paper, some common gearboxes vibration analysis methods and condition monitoring systems are explained. In addition, an experimental gearbox vibration analysis is discussed through a critical case history for a mixer gearbox related to Iran oil industry. The case history also consists of gear manufacturing (machining) recommendations, lubrication condition of gearbox and machinery maintenance activities that caused reduction in noise and vibration of the gearbox. Besides some of the recent patents and innovations in gearboxes, lubrication and vibration monitoring systems explained. Finally micro pitting and surface fatigue in pinion and bevel of mentioned horizontal to vertical gearbox discussed in details.
Keywords: Gear box, condition monitoring, time wave form (TWF), fast Fourier transform (FFT), gear mesh frequency (GMF), Shock Pulse measurement (SPM), bearing condition unit (BCU), pinion, bevel gear, micro pitting, surface fatigue.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4288217 Fault Diagnosis of Nonlinear Systems Using Dynamic Neural Networks
Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin
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This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of singleparameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.
Keywords: Hybrid fault diagnosis, Dynamic neural networks, Nonlinear systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2221216 The Accuracy of the Flight Derivative Estimates Derived from Flight Data
Authors: Jung-hoon Lee, Eung Tai Kim, Byung-hee Chang, In-hee Hwang, Dae-sung Lee
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The accuracy of estimated stability and control derivatives of a light aircraft from flight test data were evaluated. The light aircraft, named ChangGong-91, is the first certified aircraft from the Korean government. The output error method, which is a maximum likelihood estimation technique and considers measurement noise only, was used to analyze the aircraft responses measures. The multi-step control inputs were applied in order to excite the short period mode for the longitudinal and Dutch-roll mode for the lateral-directional motion. The estimated stability/control derivatives of Chan Gong-91 were analyzed for the assessment of handling qualities comparing them with those of similar aircraft. The accuracy of the flight derivative estimates derived from flight test measurement was examined in engineering judgment, scatter and Cramer-Rao bound, which turned out to be satisfactory with minor defects..Keywords: Light Aircraft, Flight Test, Accuracy, Engineering Judgment, Scatter, Cramer-Rao Bound
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1952215 Generalized Maximal Ratio Combining as a Supra-optimal Receiver Diversity Scheme
Authors: Jean-Pierre Dubois, Rania Minkara, Rafic Ayoubi
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2152214 Embedded Throughput Improving of Low-rate EDR Packets for Lower-latency
Authors: M. A. M. El-Bendary, A. E. Abu El-Azm, N. A. El-Fishawy, F. Shawky, F. E. El-Samie
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With increasing utilization of the wireless devices in different fields such as medical devices and industrial fields, the paper presents a method for simplify the Bluetooth packets with throughput enhancing. The paper studies a vital issue in wireless communications, which is the throughput of data over wireless networks. In fact, the Bluetooth and ZigBee are a Wireless Personal Area Network (WPAN). With taking these two systems competition consideration, the paper proposes different schemes for improve the throughput of Bluetooth network over a reliable channel. The proposition depends on the Channel Quality Driven Data Rate (CQDDR) rules, which determines the suitable packet in the transmission process according to the channel conditions. The proposed packet is studied over additive White Gaussian Noise (AWGN) and fading channels. The Experimental results reveal the capability of extension of the PL length by 8, 16, 24 bytes for classic and EDR packets, respectively. Also, the proposed method is suitable for the low throughput Bluetooth.Keywords: Bluetooth, throughput, adaptive packets, EDRpackets, CQDDR, low latency. Channel condition
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1901213 SNR Classification Using Multiple CNNs
Authors: Thinh Ngo, Paul Rad, Brian Kelley
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Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.Keywords: Classification, classifier fusion, CNN, Deep Learning, prediction, SNR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 720212 Medical Image Segmentation and Detection of MR Images Based on Spatial Multiple-Kernel Fuzzy C-Means Algorithm
Authors: J. Mehena, M. C. Adhikary
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In this paper, a spatial multiple-kernel fuzzy C-means (SMKFCM) algorithm is introduced for segmentation problem. A linear combination of multiples kernels with spatial information is used in the kernel FCM (KFCM) and the updating rules for the linear coefficients of the composite kernels are derived as well. Fuzzy cmeans (FCM) based techniques have been widely used in medical image segmentation problem due to their simplicity and fast convergence. The proposed SMKFCM algorithm provides us a new flexible vehicle to fuse different pixel information in medical image segmentation and detection of MR images. To evaluate the robustness of the proposed segmentation algorithm in noisy environment, we add noise in medical brain tumor MR images and calculated the success rate and segmentation accuracy. From the experimental results it is clear that the proposed algorithm has better performance than those of other FCM based techniques for noisy medical MR images.Keywords: Clustering, fuzzy C-means, image segmentation, MR images, multiple kernels.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2129211 Channel Estimation/Equalization with Adaptive Modulation and Coding over Multipath Faded Channels for WiMAX
Authors: B. Siva Kumar Reddy, B. Lakshmi
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Different order modulations combined with different coding schemes, allow sending more bits per symbol, thus achieving higher throughputs and better spectral efficiencies. However, it must also be noted that when using a modulation technique such as 64- QAM with less overhead bits, better signal-to-noise ratios (SNRs) are needed to overcome any Inter symbol Interference (ISI) and maintain a certain bit error ratio (BER). The use of adaptive modulation allows wireless technologies to yielding higher throughputs while also covering long distances. The aim of this paper is to implement an Adaptive Modulation and Coding (AMC) features of the WiMAX PHY in MATLAB and to analyze the performance of the system in different channel conditions (AWGN, Rayleigh and Rician fading channel) with channel estimation and blind equalization. Simulation results have demonstrated that the increment in modulation order causes to increment in throughput and BER values. These results derived a trade-off among modulation order, FFT length, throughput, BER value and spectral efficiency. The BER changes gradually for AWGN channel and arbitrarily for Rayleigh and Rician fade channels.
Keywords: AMC, CSI, CMA, OFDM, OFDMA, WiMAX.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3103210 Comparative Analysis of DTC Based Switched Reluctance Motor Drive Using Torque Equation and FEA Models
Authors: P. Srinivas, P. V. N. Prasad
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Since torque ripple is the main cause of noise and vibrations, the performance of Switched Reluctance Motor (SRM) can be improved by minimizing its torque ripple using a novel control technique called Direct Torque Control (DTC). In DTC technique, torque is controlled directly through control of magnitude of the flux and change in speed of the stator flux vector. The flux and torque are maintained within set hysteresis bands.
The DTC of SRM is analyzed by two methods. In one method, the actual torque is computed by conducting Finite Element Analysis (FEA) on the design specifications of the motor. In the other method, the torque is computed by Simplified Torque Equation. The variation of peak current, average current, torque ripple and speed settling time with Simplified Torque Equation model is compared with FEA based model.
Keywords: Direct Toque Control, Simplified Torque Equation, Finite Element Analysis, Torque Ripple.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3503209 Pulsation Suppression Device Design for Reciprocating Compressor
Authors: Amin Almasi
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Design and evaluation of reciprocating compressors should include a pulsation study. The object is to ensure that predicted pulsation levels meet guidelines to limit vibration, shaking forces, noise, associated pressure drops, horsepower losses and fabrication cost and time to acceptable levels. This paper explains procedures and recommendations to select and size pulsation suppression devices to obtain optimum arrangement in terms of pulsation, vibration, shaking forces, performance, reliability, safety, operation, maintenance and commercial conditions. Model and advanced formulations for pulsation study are presented. The effect of the full fluid dynamic model on the prediction of pulsation waves and resulting frequency spectrum distributions are discussed. Advanced and optimum methods of controlling pulsations are highlighted. Useful recommendations and guidelines for pulsation control, piping pulsation analysis, pulsation vessel design, shaking forces, low pressure drop orifices, pulsation study report and devices to mitigate pulsation and shaking problems are discussed.Keywords: Pulsation, Reciprocating Compressor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8835208 Mitigation of Electromagnetic Interference Generated by GPIB Control-Network in AC-DC Transfer Measurement System
Authors: M. M. Hlakola, E. Golovins, D. V. Nicolae
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The field of instrumentation electronics is undergoing an explosive growth, due to its wide range of applications. The proliferation of electrical devices in a close working proximity can negatively influence each other’s performance. The degradation in the performance is due to electromagnetic interference (EMI). This paper investigates the negative effects of electromagnetic interference originating in the General Purpose Interface Bus (GPIB) control-network of the AC-DC transfer measurement system. Remedial measures of reducing measurement errors and failure of range of industrial devices due to EMI have been explored. The ACDC transfer measurement system was analysed for the commonmode (CM) EMI effects. Further investigation of coupling path as well as much accurate identification of noise propagation mechanism has been outlined. To prevent the occurrence of common-mode (ground loops) which was identified between the GPIB system control circuit and the measurement circuit, a microcontroller-driven GPIB switching isolator device was designed, prototyped, programmed and validated. This mitigation technique has been explored to reduce EMI effectively.Keywords: CM, EMI, GPIB, ground loops.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1825207 Design and Implementation of Reed Solomon Encoder on FPGA
Authors: Amandeep Singh, Mandeep Kaur
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Error correcting codes are used for detection and correction of errors in digital communication system. Error correcting coding is based on appending of redundancy to the information message according to a prescribed algorithm. Reed Solomon codes are part of channel coding and withstand the effect of noise, interference and fading. Galois field arithmetic is used for encoding and decoding reed Solomon codes. Galois field multipliers and linear feedback shift registers are used for encoding the information data block. The design of Reed Solomon encoder is complex because of use of LFSR and Galois field arithmetic. The purpose of this paper is to design and implement Reed Solomon (255, 239) encoder with optimized and lesser number of Galois Field multipliers. Symmetric generator polynomial is used to reduce the number of GF multipliers. To increase the capability toward error correction, convolution interleaving will be used with RS encoder. The Design will be implemented on Xilinx FPGA Spartan II.
Keywords: Galois Field, Generator polynomial, LFSR, Reed Solomon.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4844206 Experimental Results about the Dynamics of the Generalized Belief Propagation Used on LDPC Codes
Authors: Jean-Christophe Sibel, Sylvain Reynal, David Declercq
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In the context of channel coding, the Generalized Belief Propagation (GBP) is an iterative algorithm used to recover the transmission bits sent through a noisy channel. To ensure a reliable transmission, we apply a map on the bits, that is called a code. This code induces artificial correlations between the bits to send, and it can be modeled by a graph whose nodes are the bits and the edges are the correlations. This graph, called Tanner graph, is used for most of the decoding algorithms like Belief Propagation or Gallager-B. The GBP is based on a non unic transformation of the Tanner graph into a so called region-graph. A clear advantage of the GBP over the other algorithms is the freedom in the construction of this graph. In this article, we explain a particular construction for specific graph topologies that involves relevant performance of the GBP. Moreover, we investigate the behavior of the GBP considered as a dynamic system in order to understand the way it evolves in terms of the time and in terms of the noise power of the channel. To this end we make use of classical measures and we introduce a new measure called the hyperspheres method that enables to know the size of the attractors.
Keywords: iterative decoder, LDPC, region-graph, chaos.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1648205 Impact of Hard Limited Clipping Crest Factor Reduction Technique on Bit Error Rate in OFDM Based Systems
Authors: Theodore Grosch, Felipe Koji Godinho Hoshino
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In wireless communications, 3GPP LTE is one of the solutions to meet the greater transmission data rate demand. One issue inherent to this technology is the PAPR (Peak-to-Average Power Ratio) of OFDM (Orthogonal Frequency Division Multiplexing) modulation. This high PAPR affects the efficiency of power amplifiers. One approach to mitigate this effect is the Crest Factor Reduction (CFR) technique. In this work, we simulate the impact of Hard Limited Clipping Crest Factor Reduction technique on BER (Bit Error Rate) in OFDM based Systems. In general, the results showed that CFR has more effects on higher digital modulation schemes, as expected. More importantly, we show the worst-case degradation due to CFR on QPSK, 16QAM, and 64QAM signals in a linear system. For example, hard clipping of 9 dB results in a 2 dB increase in signal to noise energy at a 1% BER for 64-QAM modulation.Keywords: Bit error rate, crest factor reduction, OFDM, physical layer simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2140204 Comparative Study of Different Enhancement Techniques for Computed Tomography Images
Authors: C. G. Jinimole, A. Harsha
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One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.
Keywords: Computed tomography, enhancement techniques, increasing contrast, PSNR and MSE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1378203 Stabilization of Rotational Motion of Spacecrafts Using Quantized Two Torque Inputs Based on Random Dither
Authors: Yusuke Kuramitsu, Tomoaki Hashimoto, Hirokazu Tahara
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The control problem of underactuated spacecrafts has attracted a considerable amount of interest. The control method for a spacecraft equipped with less than three control torques is useful when one of the three control torques had failed. On the other hand, the quantized control of systems is one of the important research topics in recent years. The random dither quantization method that transforms a given continuous signal to a discrete signal by adding artificial random noise to the continuous signal before quantization has also attracted a considerable amount of interest. The objective of this study is to develop the control method based on random dither quantization method for stabilizing the rotational motion of a rigid spacecraft with two control inputs. In this paper, the effectiveness of random dither quantization control method for the stabilization of rotational motion of spacecrafts with two torque inputs is verified by numerical simulations.Keywords: Spacecraft control, quantized control, nonlinear control, random dither method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 708202 Transient Population Dynamics of Phase Singularities in 2D Beeler-Reuter Model
Authors: Hidetoshi Konno, Akio Suzuki
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The paper presented a transient population dynamics of phase singularities in 2D Beeler-Reuter model. Two stochastic modelings are examined: (i) the Master equation approach with the transition rate (i.e., λ(n, t) = λ(t)n and μ(n, t) = μ(t)n) and (ii) the nonlinear Langevin equation approach with a multiplicative noise. The exact general solution of the Master equation with arbitrary time-dependent transition rate is given. Then, the exact solution of the mean field equation for the nonlinear Langevin equation is also given. It is demonstrated that transient population dynamics is successfully identified by the generalized Logistic equation with fractional higher order nonlinear term. It is also demonstrated the necessity of introducing time-dependent transition rate in the master equation approach to incorporate the effect of nonlinearity.
Keywords: Transient population dynamics, Phase singularity, Birth-death process, Non-stationary Master equation, nonlinear Langevin equation, generalized Logistic equation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1593201 High Secure Data Hiding Using Cropping Image and Least Significant Bit Steganography
Authors: Khalid A. Al-Afandy, El-Sayyed El-Rabaie, Osama Salah, Ahmed El-Mhalaway
Abstract:
This paper presents a high secure data hiding technique using image cropping and Least Significant Bit (LSB) steganography. The predefined certain secret coordinate crops will be extracted from the cover image. The secret text message will be divided into sections. These sections quantity is equal the image crops quantity. Each section from the secret text message will embed into an image crop with a secret sequence using LSB technique. The embedding is done using the cover image color channels. Stego image is given by reassembling the image and the stego crops. The results of the technique will be compared to the other state of art techniques. Evaluation is based on visualization to detect any degradation of stego image, the difficulty of extracting the embedded data by any unauthorized viewer, Peak Signal-to-Noise Ratio of stego image (PSNR), and the embedding algorithm CPU time. Experimental results ensure that the proposed technique is more secure compared with the other traditional techniques.
Keywords: Steganography, stego, LSB, crop.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1551200 Diagnosis of Multivariate Process via Nonlinear Kernel Method Combined with Qualitative Representation of Fault Patterns
Authors: Hyun-Woo Cho
Abstract:
The fault detection and diagnosis of complicated production processes is one of essential tasks needed to run the process safely with good final product quality. Unexpected events occurred in the process may have a serious impact on the process. In this work, triangular representation of process measurement data obtained in an on-line basis is evaluated using simulation process. The effect of using linear and nonlinear reduced spaces is also tested. Their diagnosis performance was demonstrated using multivariate fault data. It has shown that the nonlinear technique based diagnosis method produced more reliable results and outperforms linear method. The use of appropriate reduced space yielded better diagnosis performance. The presented diagnosis framework is different from existing ones in that it attempts to extract the fault pattern in the reduced space, not in the original process variable space. The use of reduced model space helps to mitigate the sensitivity of the fault pattern to noise.Keywords: Real-time Fault diagnosis, triangular representation of patterns in reduced spaces, Nonlinear kernel technique, multivariate statistical modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1604