Search results for: signal generator.

Authors: N. Ben Ameur, M. Loulou

Abstract:

This paper study the high-level modelling and design of delta-sigma (ΔΣ) noise shapers for audio Digital-to-Analog Converter (DAC) so as to eliminate the in-band Signal-to-Noise- Ratio (SNR) degradation that accompany one channel mismatch in audio signal. The converter combines a cascaded digital signal interpolation, a noise-shaping single loop delta-sigma modulator with a 5-bit quantizer resolution in the final stage. To reduce sensitivity of Digital-to-Analog Converter (DAC) nonlinearities of the last stage, a high pass second order Data Weighted Averaging (R2DWA) is introduced. This paper presents a MATLAB description modelling approach of the proposed DAC architecture with low distortion and swing suppression integrator designs. The ΔΣ Modulator design can be configured as a 3rd-order and allows 24-bit PCM at sampling rate of 64 kHz for Digital Video Disc (DVD) audio application. The modeling approach provides 139.38 dB of dynamic range for a 32 kHz signal band at -1.6 dBFS input signal level.

Keywords: DVD-audio, DAC, Interpolator and Interpolation Filter, Single-Loop ΔΣ Modulation, R2DWA, Clock Jitter

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Authors: Chul Ho Han, Kyoung Hoon Kim

Abstract:

This paper carries out a performance analysis based on the first and second laws of thermodynamics for heat recovery vapor generator (HRVG) of ammonia-water mixture when the heat source is low-temperature energy in the form of sensible heat. In the analysis, effects of the ammonia mass concentration and mass flow ratio of the binary mixture are investigated on the system performance including the effectiveness of heat transfer, entropy generation, and exergy efficiency. The results show that the ammonia concentration and the mass flow ratio of the mixture have significant effects on the system performance of HRVG.

Keywords: Entropy, exergy, ammonia-water mixture, heat exchanger.

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Authors: Hosein Faramarzpour

Abstract:

This work presents the optimum operational conditions for a hydrogen-based micro-scale power source, using a verified mathematical model including fluid dynamics and reaction kinetics. Thereafter, the stable operational flame regime is pursued as a key factor in optimizing the design of micro-combustors. The results show that with increasing velocities, four H2 flame regimes develop in the micro-combustor, namely: 1) periodic ignition-extinction regime, 2) steady symmetric regime, 3) pulsating asymmetric regime, and 4) steady asymmetric regime. The first regime that appears in 0.8 m/s inlet velocity is a periodic ignition-extinction regime which is characterized by counter flows and tulip-shape flames. For flow velocity above 0.2 m/s, the flame shifts downstream, and the combustion regime switches to a steady symmetric flame where temperature increases considerably due to the increased rate of incoming energy. Further elevation in flow velocity up to 1 m/s leads to the pulsating asymmetric flame formation, which is associated with pulses in various flame properties such as temperature and species concentration. Further elevation in flow velocity up to 1 m/s leads to the pulsating asymmetric flame formation, which is associated with pulses in various flame properties such as temperature and species concentration. Ultimately, when the inlet velocity reached 1.2 m/s, the last regime was observed, and a steady asymmetric regime appeared.

Keywords: Thermophotovoltaic generator, micro combustor, micro power generator, combustion regimes, flame dynamic.

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Authors: Nadheer A. Shalash, Abu Zaharin Bin Ahmad

Abstract:

Technological developments in industrial innovations have currently been related to interconnected system assistance and distribution networks. This important in order to enable an electrical load to continue receive power in the event of disconnection of load from the main power grid. This paper represents a method for reliability assessment of interconnected power systems based. The multi-agent system consists of four agents. The first agent was the generator agent to using as connected the generator to the grid depending on the state of the reserve margin and the load demand. The second was a load agent is that located at the load. Meanwhile, the third is so-called "the reverse margin agent" that to limit the reserve margin between 0 - 25% depend on the load and the unit size generator. In the end, calculation reliability Agent can be calculate expected energy not supplied (EENS), loss of load expectation (LOLE) and the effecting of tie line capacity to determine the risk levels Roy Billinton Test System (RBTS) can use to evaluated the reliability indices by using the developed JADE package. The results estimated of the reliability interconnection power systems presented in this paper. The overall reliability of power system can be improved. Thus, the market becomes more concentrated against demand increasing and the generation units were operating in relation to reliability indices. 

Keywords: Reliability indices, Load expectation, Reserve margin, Daily load, Probability, Multi-agent system.

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Authors: K. Massila, R. D. Stein, S. M. Suhaizan, A. A. Azlianor

Abstract:

A number of mass spectrometry applications are already available as web-based and windows-based systems to calculate isotope pattern and to display the mass spectrum based on the specific molecular formula besides providing necessary information. These applications were evaluated and compared with our new alternative application called Theoretical Isotope Generator (TIG) in terms of its functionality and features provided to prove this new application is working better and performing well. TIG provides extra features than others, complete with several functionality such as drawing, normalizing and zooming the generated graph that convey with the molecular information in a number of formats by providing the details of the calculation and molecules. Thus, any chemist, students, lecturers and researchers from anywhere could use TIG to gain related information on molecules and their relative intensity.

Keywords: Isotope pattern calculator, mass number, massspectrum, relative intensity.

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Authors: Parisa Shooshtari, Gelareh Mohamadi, Behnam Molaee Ardekani, Mohammad Bagher Shamsollahi

Abstract:

EEG signal is one of the oldest measures of brain activity that has been used vastly for clinical diagnoses and biomedical researches. However, EEG signals are highly contaminated with various artifacts, both from the subject and from equipment interferences. Among these various kinds of artifacts, ocular noise is the most important one. Since many applications such as BCI require online and real-time processing of EEG signal, it is ideal if the removal of artifacts is performed in an online fashion. Recently, some methods for online ocular artifact removing have been proposed. One of these methods is ARMAX modeling of EEG signal. This method assumes that the recorded EEG signal is a combination of EOG artifacts and the background EEG. Then the background EEG is estimated via estimation of ARMAX parameters. The other recently proposed method is based on adaptive filtering. This method uses EOG signal as the reference input and subtracts EOG artifacts from recorded EEG signals. In this paper we investigate the efficiency of each method for removing of EOG artifacts. A comparison is made between these two methods. Our undertaken conclusion from this comparison is that adaptive filtering method has better results compared with the results achieved by ARMAX modeling.

Keywords: Ocular Artifacts, EEG, Adaptive Filtering, ARMAX

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Authors: Kavita Burse, R.N. Yadav, S.C. Shrivastava, Vishnu Pratap Singh Kirar

Abstract:

During signal transmission, the combined effect of the transmitter filter, the transmission medium, and additive white Gaussian noise (AWGN) are included in the channel which distort and add noise to the signal. This causes the well defined signal constellation to spread causing errors in bit detection. A compact pi neural network with minimum number of nodes is proposed. The replacement of summation at each node by multiplication results in more powerful mapping. The resultant pi network is tested on six different channels.

Keywords: Additive white Gaussian noise, digitalcommunication system, multiplicative neuron, Pi neural network.

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Authors: R. Amandi, A. Shahbazi, A. Mohebi, M. Bazargan, Y. Jaberi, P. Emadi, A. Valizade

Abstract:

The application of Neural Network for disease diagnosis has made great progress and is widely used by physicians. An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which was the great motivation towards our study. In our work, tachycardia features obtained are used for the training and testing of a Neural Network. In this study we are using Fuzzy Probabilistic Neural Networks as an automatic technique for ECG signal analysis. As every real signal recorded by the equipment can have different artifacts, we needed to do some preprocessing steps before feeding it to our system. Wavelet transform is used for extracting the morphological parameters of the ECG signal. The outcome of the approach for the variety of arrhythmias shows the represented approach is superior than prior presented algorithms with an average accuracy of about %95 for more than 7 tachy arrhythmias.

Keywords: Fuzzy Logic, Probabilistic Neural Network, Tachycardia, Wavelet Transform.

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Authors: Hicham Serhoud, Djilani Benattous

Abstract:

In this paper present a sensorless maximum wind power extraction for variable speed constant frequency (VSCF) wind power generation systems with a doubly-fed induction generators (DFIG), to ensure stability and to impose the ideal feedback control solution despite of model uncertainties , using the principles of an active and reactive power controller (DPC) a robust sliding mode power control has been proposed to guarantees fast response times and precise control actions for control the active and reactive power independently. The simulation results in MATLAB/Simulink platform confirmed the good dynamic performance of power control approach for DFIGbased variable speed wind turbines.

Keywords: Doubly fed induction generator , sliding modecontrol, maximal wind energy capture, MRAS estimator

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Authors: M. Kulesza, G. Szwoch, A. Czyżewski

Abstract:

A novel approach to speech coding using the hybrid architecture is presented. Advantages of parametric and perceptual coding methods are utilized together in order to create a speech coding algorithm assuring better signal quality than in traditional CELP parametric codec. Two approaches are discussed. One is based on selection of voiced signal components that are encoded using parametric algorithm, unvoiced components that are encoded perceptually and transients that remain unencoded. The second approach uses perceptual encoding of the residual signal in CELP codec. The algorithm applied for precise transient selection is described. Signal quality achieved using the proposed hybrid codec is compared to quality of some standard speech codecs.

Keywords: CELP residual coding, hybrid codec architecture, perceptual speech coding, speech codecs comparison.

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Authors: Mahmoud Huleihil

Abstract:

In this study, the performance of a thermodynamic gas cycle of magnetohydrodynamic (MHD) power generation is considered and presented in terms of power efficiency curves. The dissipation mechanisms considered include: fluid friction modeled by means of the isentropic efficiency of the compressor, heat transfer leakage directly from the hot reservoir to the cold heat reservoir, and constant velocity of the MHD generator. The study demonstrates that power and efficiency vanish at the extremes of both slow and fast operating conditions. These points are demonstrated on power efficiency curves and the locus of efficiency at maximum power and the locus of maximum efficiency. Qualitatively, the considered loss mechanisms have a similar effect on the efficiency at maximum power operation and on maximum efficiency operation, thus these efficiencies are reduced, even for small values of the loss mechanisms.

Keywords: Magnetohydrodynamic generator, electrical efficiency, maximum power, maximum efficiency, heat engine.

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Authors: N. Zerzouri, H. Labar, S. Kechida

Abstract:

During recent years wind turbine technology has undergone rapid developments. Growth in size and the optimization of wind turbines has enabled wind energy to become increasingly competitive with conventional energy sources. As a result today-s wind turbines participate actively in the power production of several countries around the world. These developments raise a number of challenges to be dealt with now and in the future. The penetration of wind energy in the grid raises questions about the compatibility of the wind turbine power production with the grid. In particular, the contribution to grid stability, power quality and behavior during fault situations plays therefore as important a role as the reliability. In the present work, we addressed two fault situations that have shown their influence on the generator and the behavior of the wind over the defects which are briefly discussed based on simulation results.

Keywords: Doubly fed induction generator (DFIG), Wind energy, grid fault

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Authors: B. S. Raghavendra, D. Narayana Dutt

Abstract:

In this paper, we have developed a method to compute fractal dimension (FD) of discrete time signals, in the time domain, by modifying the box-counting method. The size of the box is dependent on the sampling frequency of the signal. The number of boxes required to completely cover the signal are obtained at multiple time resolutions. The time resolutions are made coarse by decimating the signal. The loglog plot of total number of boxes required to cover the curve versus size of the box used appears to be a straight line, whose slope is taken as an estimate of FD of the signal. The results are provided to demonstrate the performance of the proposed method using parametric fractal signals. The estimation accuracy of the method is compared with that of Katz, Sevcik, and Higuchi methods. In addition, some properties of the FD are discussed.

Keywords: Box-counting, Fractal dimension, Higuchi method, Katz method, Parametric fractal signals, Sevcik method.

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Authors: I.Daut, N. Gomesh, M. Irwanto, Y. M. Irwan

Abstract:

Public awareness towards green energy are on the rise and this can be prove by many product being manufactured or prerequired to be made as energy saving devices mainly to save consumer from spending more on utility billing. These schemes are popular nowadays and many homemade appliances are turned into energy saving gadget which attracts the attention of consumers. Knowing the public demands and pattern towards purchasing home appliances thus the idea of “energy saving suction hood (ESSH)" is proposed. The ESSH can be used in many places that require smoke ventilation or even to reduce the room temperature as many conventional suction hoods (CSH) do, but this device works automatically by the usage of sensors that detects the smoke/temperature and automatically spins the exhaust fan. As it turns, the mechanical rotation rotates the AC generator which is coupled together with the fan and then charges the battery. The innovation of this product is, it does not rely on the utility supply as it is also hook up with a solar panel which also charges the battery, Secondly, it generates energy as the exhaust fan mechanically rotates. Thirdly, an energy loop back feature is introduced to this system which will supply for the ventilator fan. Another major innovation is towards interfacing this device with an in house production of generator. This generator is produced by proper design on stator as well as rotor to reduce the losses. A comparison is made between the ESSH and the CSH and result shows that the ESSH saves 172.8kWh/year of utility supply which is used by CSH. This amount of energy can save RM 3.14 from monthly utility bill and a total of RM 37.67 per year. In fact this product can generate 175 Watt of power from generator(75W) and solar panel(100W) that can be used either to supply other household appliances and/or to loop back to supply the fans motor. The innovation of this system is essential for future production of other equipment by using the loopback power method and turning most equipment into a standalone system.

Keywords: Energy saving suction hood (ESSH), conventional suction hoods (CSH), energy, and power

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Authors: Panos Kotsas

Abstract:

This paper presents the application of a signal intensity independent registration criterion for non-rigid body registration of medical images. The criterion is defined as the weighted ratio image of two images. The ratio is computed on a voxel per voxel basis and weighting is performed by setting the ratios between signal and background voxels to a standard high value. The mean squared value of the weighted ratio is computed over the union of the signal areas of the two images and it is minimized using the Chebyshev polynomial approximation. The geometric transformation model adopted is a local cubic B-splines based model.

Keywords: Medical image, non-rigid, registration.

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Authors: R. Latif, W. Jenkal, A. Toumanari, A. Hatim

Abstract:

This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.

Keywords: Hybrid technique, ADTF, DWT, tresholding, ECG signal.

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Authors: Hamza Nejib, Okba Taouali

Abstract:

This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: KLMS, online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS.

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Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

Abstract:

The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: Acoustic model, direction of arrival, inverse source problem, sound localization, urban noises.

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Authors: Raja Singh Khela, R. K. Bansal, K. S. Sandhu, A. K. Goel

Abstract:

Self-Excited Induction Generator (SEIG) builds up voltage while it enters in its magnetic saturation region. Due to non-linear magnetic characteristics, the performance analysis of SEIG involves cumbersome mathematical computations. The dependence of air-gap voltage on saturated magnetizing reactance can only be established at rated frequency by conducting a laboratory test commonly known as synchronous run test. But, there is no laboratory method to determine saturated magnetizing reactance and air-gap voltage of SEIG at varying speed, terminal capacitance and other loading conditions. For overall analysis of SEIG, prior information of magnetizing reactance, generated frequency and air-gap voltage is essentially required. Thus, analytical methods are the only alternative to determine these variables. Non-existence of direct mathematical relationship of these variables for different terminal conditions has forced the researchers to evolve new computational techniques. Artificial Neural Networks (ANNs) are very useful for solution of such complex problems, as they do not require any a priori information about the system. In this paper, an attempt is made to use cascaded neural networks to first determine the generated frequency and magnetizing reactance with varying terminal conditions and then air-gap voltage of SEIG. The results obtained from the ANN model are used to evaluate the overall performance of SEIG and are found to be in good agreement with experimental results. Hence, it is concluded that analysis of SEIG can be carried out effectively using ANNs.

Keywords: Self-Excited Induction Generator, Artificial NeuralNetworks, Exciting Capacitance and Saturated magnetizingreactance.

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Authors: Nileshkumar Vaishnav, Aditya Tatu

Abstract:

An algebraic framework for processing graph signals axiomatically designates the graph adjacency matrix as the shift operator. In this setup, we often encounter a problem wherein we know the filtered output and the filter coefficients, and need to find out the input graph signal. Solution to this problem using direct approach requires O(N3) operations, where N is the number of vertices in graph. In this paper, we adapt the spectral graph partitioning method for partitioning of graphs and use it to reduce the computational cost of the filtering problem. We use the example of denoising of the temperature data to illustrate the efficacy of the approach.

Keywords: Graph signal processing, graph partitioning, inverse filtering on graphs, algebraic signal processing.

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Authors: H. N. Suresh, Dr. V. Udaya Shankara

Abstract:

A technique proposed for the automatic detection of spikes in electroencephalograms (EEG). A multi-resolution approach and a non-linear energy operator are exploited. The signal on each EEG channel is decomposed into three sub bands using a non-decimated wavelet transform (WT). The WT is a powerful tool for multi-resolution analysis of non-stationary signal as well as for signal compression, recognition and restoration. Each sub band is analyzed by using a non-linear energy operator, in order to detect spikes. A decision rule detects the presence of spikes in the EEG, relying upon the energy of the three sub-bands. The effectiveness of the proposed technique was confirmed by analyzing both test signals and EEG layouts.

Keywords: EEG, Spike, SNEO, Wavelet Transform

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Authors: Abhijit Mitra, Bhargav Kumar Mitra, Biswajoy Chatterjee

Abstract:

We present a novel scheme to recognize isolated speech signals using certain statistical parameters derived from those signals. The determination of the statistical estimates is based on extracted signal information rather than the original signal information in order to reduce the computational complexity. Subtle details of these estimates, after extracting the speech signal from ambience noise, are first exploited to segregate the polysyllabic words from the monosyllabic ones. Precise recognition of each distinct word is then carried out by analyzing the histogram, obtained from these information.

Keywords: Isolated speech signals, Block overlapping technique, Positive peaks, Histogram analysis.

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Authors: Azeemsha Thacham Poyil, Nasimudeen KM

Abstract:

This research paper presents some methods to assess the performance of Wigner Ville Distribution for Time-Frequency representation of non-stationary signals, in comparison with the other representations like STFT, Spectrogram etc. The simultaneous timefrequency resolution of WVD is one of the important properties which makes it preferable for analysis and detection of linear FM and transient signals. There are two algorithms proposed here to assess the resolution and to compare the performance of signal detection. First method is based on the measurement of area under timefrequency plot; in case of a linear FM signal analysis. A second method is based on the instantaneous power calculation and is used in case of transient, non-stationary signals. The implementation is explained briefly for both methods with suitable diagrams. The accuracy of the measurements is validated to show the better performance of WVD representation in comparison with STFT and Spectrograms.

Keywords: WVD: Wigner Ville Distribution, STFT: Short Time Fourier Transform, FT: Fourier Transform, TFR: Time-Frequency Representation, FM: Frequency Modulation, LFM Signal: Linear FM Signal, JTFA: Joint time frequency analysis.

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Authors: Panos Kotsas, Tony Dodd

Abstract:

This paper presents the application of a signal intensity independent similarity criterion for rigid and non-rigid body registration of binary objects. The criterion is defined as the weighted ratio image of two images. The ratio is computed on a voxel per voxel basis and weighting is performed by setting the raios between signal and background voxels to a standard high value. The mean squared value of the weighted ratio is computed over the union of the signal areas of the two images and it is minimized using the Chebyshev polynomial approximation.

Keywords: rigid and non-rigid body registration, binary objects

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Authors: Durgesh Kumar Ojha, Monica Subashini

Abstract:

The proposed method is to study and analyze Electrocardiograph (ECG) waveform to detect abnormalities present with reference to P, Q, R and S peaks. The first phase includes the acquisition of real time ECG data. In the next phase, generation of signals followed by pre-processing. Thirdly, the procured ECG signal is subjected to feature extraction. The extracted features detect abnormal peaks present in the waveform Thus the normal and abnormal ECG signal could be differentiated based on the features extracted. The work is implemented in the most familiar multipurpose tool, MATLAB. This software efficiently uses algorithms and techniques for detection of any abnormalities present in the ECG signal. Proper utilization of MATLAB functions (both built-in and user defined) can lead us to work with ECG signals for processing and analysis in real time applications. The simulation would help in improving the accuracy and the hardware could be built conveniently.

Keywords: ECG Waveform, Peak Detection, Arrhythmia, Matlab.

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Authors: I. Omerhodzic, S. Avdakovic, A. Nuhanovic, K. Dizdarevic

Abstract:

In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the seizure). First, the Discrete Wavelet Transform (DWT) with the Multi-Resolution Analysis (MRA) is applied to decompose EEG signal at resolution levels of the components of the EEG signal (δ, θ, α, β and γ) and the Parseval-s theorem are employed to extract the percentage distribution of energy features of the EEG signal at different resolution levels. Second, the neural network (NN) classifies these extracted features to identify the EEGs type according to the percentage distribution of energy features. The performance of the proposed algorithm has been evaluated using in total 300 EEG signals. The results showed that the proposed classifier has the ability of recognizing and classifying EEG signals efficiently.

Keywords: Epilepsy, EEG, Wavelet transform, Energydistribution, Neural Network, Classification.

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Authors: R. Sarathi, G. Koperundevi

Abstract:

Design of Converter transformer insulation is a major challenge. The insulation of these transformers is stressed by both AC and DC voltages. Particle contamination is one of the major problems in insulation structures, as they generate partial discharges leading it to major failure of insulation. Similarly corona discharges occur in transformer insulation. This partial discharge due to particle movement / corona formation in insulation structure under different voltage wave shapes, are different. In the present study, UHF technique is adopted to understand the discharge activity and could be realized that the characteristics of UHF signal generated under low and high fields are different. In the case of corona generated signal, the frequency content of the UHF sensor output lies in the range 0.3-1.2 GHz and is not much varied except for its increase in magnitude of discharge with the increase in applied voltage. It is realized that the current signal injected due to partial discharges/corona is about 4ns duration measured for first one half cycle. Wavelet technique is adopted in the present study. It allows one to identify the frequency content present in the signal at different instant of time. The STD-MRA analysis helps one to identify the frequency band in which the energy content of the UHF signal is maximum.

Keywords: Contamination, Insulation, Partial Discharges, Transformer oil, UHF sensors.

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Authors: Mario Mastriani, Marcelo Naiouf

Abstract:

The Gram-Schmidt Process (GSP) is used to convert a non-orthogonal basis (a set of linearly independent vectors) into an orthonormal basis (a set of orthogonal, unit-length vectors). The process consists of taking each vector and then subtracting the elements in common with the previous vectors. This paper introduces an Enhanced version of the Gram-Schmidt Process (EGSP) with inverse, which is useful for signal and image processing applications.

Keywords: Digital filters, digital signal and image processing, Gram-Schmidt Process, orthonormalization.

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Authors: Kyaw Myo Lin

Abstract:

This paper presents small signal stability study carried over the 140-Bus, 31-Machine, 5-Area MEPE system and validated on free and open source software: PSAT. Well-established linearalgebra analysis, eigenvalue analysis, is employed to determine the small signal dynamic behavior of test system. The aspects of local and interarea oscillations which may affect the operation and behavior of power system are analyzed. Eigenvalue analysis is carried out to investigate the small signal behavior of test system and the participation factors have been determined to identify the participation of the states in the variation of different mode shapes. Also, the variations in oscillatory modes are presented to observe the damping performance of the test system.

Keywords: Eigenvalue analysis, Mode shapes, MEPE test system, Participation factors, Power System oscillations.

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Authors: K. M. Doraiswamy, Lakshminarayana Merugu, B. C. Jinaga

Abstract:

This paper explains the cause of nonlinearity in floor attenuation hither to left unexplained. The performance degradation occurring in air interface for GSM signals is quantitatively analysed using the concept of Radiating Columns of buildings. The signal levels were measured using Wireless Network Optimising Drive Test Tool (E6474A of Agilent Technologies). The measurements were taken in reflected signal environment under usual fading conditions on actual GSM signals radiated from base stations. A mathematical model is derived from the measurements to predict the GSM signal levels in different floors. It was applied on three buildings and found that the predicted signal levels deviated from the measured levels with in +/- 2 dB for all floors. It is more accurate than the prediction models based on Floor Attenuation Factor. It can be used for planning proper indoor coverage in multi storey buildings.

Keywords: GSM air interface, nonlinear attenuation, multistory building, radiating columns, ground conduction and floor attenuation factor.

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