Search results for: Semi-classical signal analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9458

Search results for: Semi-classical signal analysis

9368 Detection of Power Quality Disturbances using Wavelet Transform

Authors: Sudipta Nath, Arindam Dey, Abhijit Chakrabarti

Abstract:

This paper presents features that characterize power quality disturbances from recorded voltage waveforms using wavelet transform. The discrete wavelet transform has been used to detect and analyze power quality disturbances. The disturbances of interest include sag, swell, outage and transient. A power system network has been simulated by Electromagnetic Transients Program. Voltage waveforms at strategic points have been obtained for analysis, which includes different power quality disturbances. Then wavelet has been chosen to perform feature extraction. The outputs of the feature extraction are the wavelet coefficients representing the power quality disturbance signal. Wavelet coefficients at different levels reveal the time localizing information about the variation of the signal.

Keywords: Power quality, detection of disturbance, wavelet transform, multiresolution signal decomposition.

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9367 Detection of Clipped Fragments in Speech Signals

Authors: Sergei Aleinik, Yuri Matveev

Abstract:

In this paper a novel method for the detection of  clipping in speech signals is described. It is shown that the new  method has better performance than known clipping detection  methods, is easy to implement, and is robust to changes in signal  amplitude, size of data, etc. Statistical simulation results are  presented.

 

Keywords: Clipping, clipped signal, speech signal processing.

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9366 New Iterative Algorithm for Improving Depth Resolution in Ionic Analysis: Effect of Iterations Number

Authors: N. Dahraoui, M. Boulakroune, D. Benatia

Abstract:

In this paper, the improvement by deconvolution of the depth resolution in Secondary Ion Mass Spectrometry (SIMS) analysis is considered. Indeed, we have developed a new Tikhonov- Miller deconvolution algorithm where a priori model of the solution is included. This is a denoisy and pre-deconvoluted signal obtained from: firstly, by the application of wavelet shrinkage algorithm, secondly by the introduction of the obtained denoisy signal in an iterative deconvolution algorithm. In particular, we have focused the light on the effect of the iterations number on the evolution of the deconvoluted signals. The SIMS profiles are multilayers of Boron in Silicon matrix.

Keywords: DRF, in-depth resolution, multiresolution deconvolution, SIMS, wavelet shrinkage.

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9365 A Signal Driven Adaptive Resolution Short-Time Fourier Transform

Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin

Abstract:

The frequency contents of the non-stationary signals vary with time. For proper characterization of such signals, a smart time-frequency representation is necessary. Classically, the STFT (short-time Fourier transform) is employed for this purpose. Its limitation is the fixed timefrequency resolution. To overcome this drawback an enhanced STFT version is devised. It is based on the signal driven sampling scheme, which is named as the cross-level sampling. It can adapt the sampling frequency and the window function (length plus shape) by following the input signal local variations. This adaptation results into the proposed technique appealing features, which are the adaptive time-frequency resolution and the computational efficiency.

Keywords: Level Crossing Sampling, Activity Selection, Adaptive Resolution Analysis, Computational Complexity.

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9364 Flexible Sensor Array with Programmable Measurement System

Authors: Jung-Chuan Chou, Wei-Chuan Chen, Chien-Cheng Chen

Abstract:

This study is concerned with pH solution detection using 2 × 4 flexible sensor array based on a plastic polyethylene terephthalate (PET) substrate that is coated a conductive layer and a ruthenium dioxide (RuO2) sensitive membrane with the technologies of screen-printing and RF sputtering. For data analysis, we also prepared a dynamic measurement system for acquiring the response voltage and analyzing the characteristics of the working electrodes (WEs), such as sensitivity and linearity. In this condition, an array measurement system was designed to acquire the original signal from sensor array, and it is based on the method of digital signal processing (DSP). The DSP modifies the unstable acquisition data to a direct current (DC) output using the technique of digital filter. Hence, this sensor array can obtain a satisfactory yield, 62.5%, through the design measurement and analysis system in our laboratory.

Keywords: Flexible sensor array, PET, RuO2, dynamic measurement, data analysis.

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9363 Kurtosis, Renyi's Entropy and Independent Component Scalp Maps for the Automatic Artifact Rejection from EEG Data

Authors: Antonino Greco, Nadia Mammone, Francesco Carlo Morabito, Mario Versaci

Abstract:

The goal of this work is to improve the efficiency and the reliability of the automatic artifact rejection, in particular from the Electroencephalographic (EEG) recordings. Artifact rejection is a key topic in signal processing. The artifacts are unwelcome signals that may occur during the signal acquisition and that may alter the analysis of the signals themselves. A technique for the automatic artifact rejection, based on the Independent Component Analysis (ICA) for the artifact extraction and on some high order statistics such as kurtosis and Shannon-s entropy, was proposed some years ago in literature. In this paper we enhance this technique introducing the Renyi-s entropy. The performance of our method was tested exploiting the Independent Component scalp maps and it was compared to the performance of the method in literature and it showed to outperform it.

Keywords: Artifact, EEG, Renyi's entropy, independent component analysis, kurtosis.

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9362 Efficiency of Different GLR Test-statistics for Spatial Signal Detection

Authors: Olesya Bolkhovskaya, Alexander Maltsev

Abstract:

In this work the characteristics of spatial signal detec¬tion from an antenna array in various sample cases are investigated. Cases for a various number of available prior information about the received signal and the background noise are considered. The spatial difference between a signal and noise is only used. The performance characteristics and detecting curves are presented. All test-statistics are obtained on the basis of the generalized likelihood ratio (GLR). The received results are correct for a short and long sample.

Keywords: GLR test-statistic, detection task, generalized likelihood ratio, antenna array, detection curves, performance characteristics.

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9361 Noise Removal from Surface Respiratory EMG Signal

Authors: Slim Yacoub, Kosai Raoof

Abstract:

The aim of this study was to remove the two principal noises which disturb the surface electromyography signal (Diaphragm). These signals are the electrocardiogram ECG artefact and the power line interference artefact. The algorithm proposed focuses on a new Lean Mean Square (LMS) Widrow adaptive structure. These structures require a reference signal that is correlated with the noise contaminating the signal. The noise references are then extracted : first with a noise reference mathematically constructed using two different cosine functions; 50Hz (the fundamental) function and 150Hz (the first harmonic) function for the power line interference and second with a matching pursuit technique combined to an LMS structure for the ECG artefact estimation. The two removal procedures are attained without the use of supplementary electrodes. These techniques of filtering are validated on real records of surface diaphragm electromyography signal. The performance of the proposed methods was compared with already conducted research results.

Keywords: Surface EMG, Adaptive, Matching Pursuit, Powerline interference.

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9360 Blind Non-Minimum Phase Channel Identification Using 3rd and 4th Order Cumulants

Authors: S. Safi, A. Zeroual

Abstract:

In this paper we propose a family of algorithms based on 3rd and 4th order cumulants for blind single-input single-output (SISO) Non-Minimum Phase (NMP) Finite Impulse Response (FIR) channel estimation driven by non-Gaussian signal. The input signal represents the signal used in 10GBASE-T (or IEEE 802.3an-2006) as a Tomlinson-Harashima Precoded (THP) version of random Pulse-Amplitude Modulation with 16 discrete levels (PAM-16). The proposed algorithms are tested using three non-minimum phase channel for different Signal-to-Noise Ratios (SNR) and for different data input length. Numerical simulation results are presented to illustrate the performance of the proposed algorithms.

Keywords: Higher Order Cumulants, Channel identification, Ethernet communication.

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9359 Power Integrity Analysis of Power Delivery System in High Speed Digital FPGA Board

Authors: Anil Kumar Pandey

Abstract:

Power plane noise is the most significant source of signal integrity (SI) issues in a high-speed digital design. In this paper, power integrity (PI) analysis of multiple power planes in a power delivery system of a 12-layer high-speed FPGA board is presented. All 10 power planes of HSD board are analyzed separately by using 3D Electromagnetic based PI solver, then the transient simulation is performed on combined PI data of all planes along with voltage regulator modules (VRMs) and 70 current drawing chips to get the board level power noise coupling on different high-speed signals. De-coupling capacitors are placed between power planes and ground to reduce power noise coupling with signals.

Keywords: Channel simulation, electromagnetic simulation, power-aware signal integrity analysis, power integrity, PIPro.

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9358 Sensitivity Analysis for Direction of Arrival Estimation Using Capon and Music Algorithms in Mobile Radio Environment

Authors: Mustafa Abdalla, Khaled A. Madi, Rajab Farhat

Abstract:

An array antenna system with innovative signal processing can improve the resolution of a source direction of arrival (DoA) estimation. High resolution techniques take the advantage of array antenna structures to better process the incoming waves. They also have the capability to identify the direction of multiple targets. This paper investigates performance of the DOA estimation algorithm namely; Capon and MUSIC on the uniform linear array (ULA). The simulation results show that in Capon and MUSIC algorithm the resolution of the DOA techniques improves as number of snapshots, number of array elements, signal-to-noise ratio and separation angle between the two sources θ increases.

Keywords: Antenna array, Capon, MUSIC, Direction-of-arrival estimation, signal processing, uniform linear arrays.

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9357 Parameters Extraction for Pseudomorphic HEMTs Using Genetic Algorithms

Authors: Mazhar B. Tayel, Amr H. Yassin

Abstract:

A proposed small-signal model parameters for a pseudomorphic high electron mobility transistor (PHEMT) is presented. Both extrinsic and intrinsic circuit elements of a smallsignal model are determined using genetic algorithm (GA) as a stochastic global search and optimization tool. The parameters extraction of the small-signal model is performed on 200-μm gate width AlGaAs/InGaAs PHEMT. The equivalent circuit elements for a proposed 18 elements model are determined directly from the measured S- parameters. The GA is used to extract the parameters of the proposed small-signal model from 0.5 up to 18 GHz.

Keywords: PHEMT, Genetic Algorithms, small signal modeling, optimization.

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9356 Compressed Sensing of Fetal Electrocardiogram Signals Based on Joint Block Multi-Orthogonal Least Squares Algorithm

Authors: Xiang Jianhong, Wang Cong, Wang Linyu

Abstract:

With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal electrocardiogram, compressed sensing, joint sparse reconstruction, block sparse signal

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9355 Generic Filtering of Infinite Sets of Stochastic Signals

Authors: Anatoli Torokhti, Phil Howlett

Abstract:

A theory for optimal filtering of infinite sets of random signals is presented. There are several new distinctive features of the proposed approach. First, a single optimal filter for processing any signal from a given infinite signal set is provided. Second, the filter is presented in the special form of a sum with p terms where each term is represented as a combination of three operations. Each operation is a special stage of the filtering aimed at facilitating the associated numerical work. Third, an iterative scheme is implemented into the filter structure to provide an improvement in the filter performance at each step of the scheme. The final step of the scheme concerns signal compression and decompression. This step is based on the solution of a new rank-constrained matrix approximation problem. The solution to the matrix problem is described in this paper. A rigorous error analysis is given for the new filter.

Keywords: Optimal filtering, data compression, stochastic signals.

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9354 Improved Approximation to the Derivative of a Digital Signal Using Wavelet Transforms for Crosstalk Analysis

Authors: S. P. Kozaitis, R. L. Kriner

Abstract:

The information revealed by derivatives can help to better characterize digital near-end crosstalk signatures with the ultimate goal of identifying the specific aggressor signal. Unfortunately, derivatives tend to be very sensitive to even low levels of noise. In this work we approximated the derivatives of both quiet and noisy digital signals using a wavelet-based technique. The results are presented for Gaussian digital edges, IBIS Model digital edges, and digital edges in oscilloscope data captured from an actual printed circuit board. Tradeoffs between accuracy and noise immunity are presented. The results show that the wavelet technique can produce first derivative approximations that are accurate to within 5% or better, even under noisy conditions. The wavelet technique can be used to calculate the derivative of a digital signal edge when conventional methods fail.

Keywords: digital signals, electronics, IBIS model, printedcircuit board, wavelets

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9353 Realization of a Temperature Based Automatic Controlled Domestic Electric Boiling System

Authors: Shengqi Yu, Jinwei Zhao

Abstract:

This paper presents a kind of analog circuit based temperature control system, which is mainly composed by threshold control signal circuit, synchronization signal circuit and trigger pulse circuit. Firstly, the temperature feedback signal function is realized by temperature sensor TS503F3950E. Secondly, the main control circuit forms the cycle controlled pulse signal to control the thyristor switching model. Finally two reverse paralleled thyristors regulate the output power by their switching state. In the consequence, this is a modernized and energy-saving domestic electric heating system.

Keywords: Time base circuit, automatic control, zero-crossing trigger, temperature control.

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9352 The Autoregresive Analysis for Wind Turbine Signal Postprocessing

Authors: Daniel Pereiro, Felix Martinez, Iker Urresti, Ana Gomez Gonzalez

Abstract:

Today modern simulations solutions in the wind turbine industry have achieved a high degree of complexity and detail in result. Limitations exist when it is time to validate model results against measurements. Regarding Model validation it is of special interest to identify mode frequencies and to differentiate them from the different excitations. A wind turbine is a complex device and measurements regarding any part of the assembly show a lot of noise. Input excitations are difficult or even impossible to measure due to the stochastic nature of the environment. Traditional techniques for frequency analysis or features extraction are widely used to analyze wind turbine sensor signals, but have several limitations specially attending to non stationary signals (Events). A new technique based on autoregresive analysis techniques is introduced here for a specific application, a comparison and examples related to different events in the wind turbine operations are presented.

Keywords: Wind turbine, signal processing, mode extraction.

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9351 Complex Energy Signal Model for Digital Human Fingerprint Matching

Authors: Jason Zalev, Reza Sedaghat

Abstract:

This paper describes a complex energy signal model that is isomorphic with digital human fingerprint images. By using signal models, the problem of fingerprint matching is transformed into the signal processing problem of finding a correlation between two complex signals that differ by phase-rotation and time-scaling. A technique for minutiae matching that is independent of image translation, rotation and linear-scaling, and is resistant to missing minutiae is proposed. The method was tested using random data points. The results show that for matching prints the scaling and rotation angles are closely estimated and a stronger match will have a higher correlation.

Keywords: Affine Invariant, Fingerprint Recognition, Matching, Minutiae.

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9350 Collective Oscillations in a Magnetized Plasma Subjected to a Radiation Field

Authors: Daniel Santos, Bruno Ribeiro, Marco Amato, Antonio Fonseca

Abstract:

In this paper we discuss the behaviour of the longitudinal modes of a magnetized non collisional plasma subjected to an external electromagnetic field. We apply a semiclassical formalism, with the electrons being studied in a quantum mechanical viewpoint whereas the electromagnetic field in the classical context. We calculate the dielectric function in order to obtains the modes and found that, unlike the Bernstein modes, the presence of radiation induces oscillations around the cyclotron harmonics, which are smoothed as the energy stored in the radiation field becomes small compared to the thermal energy of the electrons. We analyze the influence of the number of photon involved in the electronic transitions between the Landau levels and how the parameters such as the external fields strength, plasma density and temperature affect the dispersion relation

Keywords: Collective oscillations, External fields, Dispersion relation.

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9349 Decoy-pulse Protocol for Frequency-coded Quantum Key Distribution

Authors: Sudeshna Bhattacharya, Pratyush Pandey, Pradeep Kumar K

Abstract:

We propose a decoy-pulse protocol for frequency-coded implementation of B92 quantum key distribution protocol. A direct extension of decoy-pulse method to frequency-coding scheme results in security loss as an eavesdropper can distinguish between signal and decoy pulses by measuring the carrier photon number without affecting other statistics. We overcome this problem by optimizing the ratio of carrier photon number of decoy-to-signal pulse to be as close to unity as possible. In our method the switching between signal and decoy pulses is achieved by changing the amplitude of RF signal as opposed to modulating the intensity of optical signal thus reducing system cost. We find an improvement by a factor of 100 approximately in the key generation rate using decoy-state protocol. We also study the effect of source fluctuation on key rate. Our simulation results show a key generation rate of 1.5×10-4/pulse for link lengths up to 70km. Finally, we discuss the optimum value of average photon number of signal pulse for a given key rate while also optimizing the carrier ratio.

Keywords: B92, decoy-pulse, frequency-coding, quantum key distribution.

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9348 LTE Performance Analysis in the City of Bogota Northern Zone for Two Different Mobile Broadband Operators over Qualipoc

Authors: Víctor D. Rodríguez, Edith P. Estupiñán, Juan C. Martínez

Abstract:

The evolution in mobile broadband technologies has allowed to increase the download rates in users considering the current services. The evaluation of technical parameters at the link level is of vital importance to validate the quality and veracity of the connection, thus avoiding large losses of data, time and productivity. Some of these failures may occur between the eNodeB (Evolved Node B) and the user equipment (UE), so the link between the end device and the base station can be observed. LTE (Long Term Evolution) is considered one of the IP-oriented mobile broadband technologies that work stably for data and VoIP (Voice Over IP) for those devices that have that feature. This research presents a technical analysis of the connection and channeling processes between UE and eNodeB with the TAC (Tracking Area Code) variables, and analysis of performance variables (Throughput, Signal to Interference and Noise Ratio (SINR)). Three measurement scenarios were proposed in the city of Bogotá using QualiPoc, where two operators were evaluated (Operator 1 and Operator 2). Once the data were obtained, an analysis of the variables was performed determining that the data obtained in transmission modes vary depending on the parameters BLER (Block Error Rate), performance and SNR (Signal-to-Noise Ratio). In the case of both operators, differences in transmission modes are detected and this is reflected in the quality of the signal. In addition, due to the fact that both operators work in different frequencies, it can be seen that Operator 1, despite having spectrum in Band 7 (2600 MHz), together with Operator 2, is reassigning to another frequency, a lower band, which is AWS (1700 MHz), but the difference in signal quality with respect to the establishment with data by the provider Operator 2 and the difference found in the transmission modes determined by the eNodeB in Operator 1 is remarkable.

Keywords: BLER, LTE, Network, Qualipoc, SNR.

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9347 Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP) for Recovering Signal

Authors: Israa Sh. Tawfic, Sema Koc Kayhan

Abstract:

Given a large sparse signal, great wishes are to reconstruct the signal precisely and accurately from lease number of measurements as possible as it could. Although this seems possible by theory, the difficulty is in built an algorithm to perform the accuracy and efficiency of reconstructing. This paper proposes a new proved method to reconstruct sparse signal depend on using new method called Least Support Matching Pursuit (LS-OMP) merge it with the theory of Partial Knowing Support (PSK) given new method called Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP). The new methods depend on the greedy algorithm to compute the support which depends on the number of iterations. So to make it faster, the PKLS-OMP adds the idea of partial knowing support of its algorithm. It shows the efficiency, simplicity, and accuracy to get back the original signal if the sampling matrix satisfies the Restricted Isometry Property (RIP). Simulation results also show that it outperforms many algorithms especially for compressible signals.

Keywords: Compressed sensing, Lest Support Orthogonal Matching Pursuit, Partial Knowing Support, Restricted isometry property, signal reconstruction.

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9346 An Improved Total Variation Regularization Method for Denoising Magnetocardiography

Authors: Yanping Liao, Congcong He, Ruigang Zhao

Abstract:

The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: Constraint parameters, derivative matrix, magnetocardiography, regular term, total variation.

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9345 Self-Sensing versus Reference Air Gaps

Authors: Alexander Schulz, Ingrid Rottensteiner, Manfred Neumann, Michael Wehse, Johann Wassermann

Abstract:

Self-sensing estimates the air gap within an electro magnetic path by analyzing the bearing coil current and/or voltage waveform. The self-sensing concept presented in this paper has been developed within the research project “Active Magnetic Bearings with Supreme Reliability" and is used for position sensor fault detection. Within this new concept gap calculation is carried out by an alldigital analysis of the digitized coil current and voltage waveform. For analysis those time periods within the PWM period are used, which give the best results. Additionally, the concept allows the digital compensation of nonlinearities, for example magnetic saturation, without degrading signal quality. This increases the accuracy and robustness of the air gap estimation and additionally reduces phase delays. Beneath an overview about the developed concept first measurement results are presented which show the potential of this all-digital self-sensing concept.

Keywords: digital signal analysis, active magnetic bearing, reliability, fault detection.

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9344 Application of Mutual Information based Least dependent Component Analysis (MILCA) for Removal of Ocular Artifacts from Electroencephalogram

Authors: V Krishnaveni, S Jayaraman, K Ramadoss

Abstract:

The electrical potentials generated during eye movements and blinks are one of the main sources of artifacts in Electroencephalogram (EEG) recording and can propagate much across the scalp, masking and distorting brain signals. In recent times, signal separation algorithms are used widely for removing artifacts from the observed EEG data. In this paper, a recently introduced signal separation algorithm Mutual Information based Least dependent Component Analysis (MILCA) is employed to separate ocular artifacts from EEG. The aim of MILCA is to minimize the Mutual Information (MI) between the independent components (estimated sources) under a pure rotation. Performance of this algorithm is compared with eleven popular algorithms (Infomax, Extended Infomax, Fast ICA, SOBI, TDSEP, JADE, OGWE, MS-ICA, SHIBBS, Kernel-ICA, and RADICAL) for the actual independence and uniqueness of the estimated source components obtained for different sets of EEG data with ocular artifacts by using a reliable MI Estimator. Results show that MILCA is best in separating the ocular artifacts and EEG and is recommended for further analysis.

Keywords: Electroencephalogram, Ocular Artifacts (OA), Independent Component Analysis (ICA), Mutual Information (MI), Mutual Information based Least dependent Component Analysis(MILCA)

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9343 Quality Factor Variation with Transform Order in Fractional Fourier Domain

Authors: Sukrit Shankar, Chetana Shanta Patsa, K. Pardha Saradhi, Jaydev Sharma

Abstract:

Fractional Fourier Transform is a powerful tool, which is a generalization of the classical Fourier Transform. This paper provides a mathematical relation relating the span in Fractional Fourier domain with the amplitude and phase functions of the signal, which is further used to study the variation of quality factor with different values of the transform order. It is seen that with the increase in the number of transients in the signal, the deviation of average Fractional Fourier span from the frequency bandwidth increases. Also, with the increase in the transient nature of the signal, the optimum value of transform order can be estimated based on the quality factor variation, and this value is found to be very close to that for which one can obtain the most compact representation. With the entire mathematical analysis and experimentation, we consolidate the fact that Fractional Fourier Transform gives more optimal representations for a number of transform orders than Fourier transform.

Keywords: Fractional Fourier Transform, Quality Factor, Fractional Fourier span, transient signals.

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9342 Stable Delta-Sigma Modulator with Signal Dependent Forward Path Gain for Industrial Applications

Authors: K. Diwakar, K. Aanandha Saravanan, C. Senthilpari

Abstract:

Higher order ΔΣ Modulator (DSM) is basically an unstable system. The approximate conditions for stability cannot be used for the design of a DSM for industrial applications where risk is involved. The existing second order, single stage, single bit, unity feedback gain , discrete DSM cannot be used for the normalized full range (-1 to +1) of an input signal since the DSM becomes unstable when the input signal is above ±0.55. The stability is also not guaranteed for input signals of amplitude less than ±0.55. In the present paper, the above mentioned second order DSM is modified with input signal dependent forward path gain. The proposed DSM is suitable for industrial applications where one needs the digital representation of the analog input signal, during each sampling period. The proposed DSM can operate almost for the full range of input signals (-0.95 to +0.95) without causing instability, assuming that the second integrator output should not exceed the circuit supply voltage, ±15 Volts.

Keywords: DSM, stability, SNR, state variables.

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9341 Optical Heterodyning of Injection-Locked Laser Sources — A Novel Technique for Millimeter-Wave Signal Generation

Authors: Subal Kar, Madhuja Ghosh, Soumik Das, Antara Saha

Abstract:

A novel technique has been developed to generate ultra-stable millimeter-wave signal by optical heterodyning of the output from two slave laser (SL) sources injection-locked to the sidebands of a frequency modulated (FM) master laser (ML). Precise thermal tuning of the SL sources is required to lock the particular slave laser frequency to the desired FM sidebands of the ML. The output signals from the injection-locked SL when coherently heterodyned in a fast response photo detector like high electron mobility transistor (HEMT), extremely stable millimeter-wave signal having very narrow line width can be generated. The scheme may also be used to generate ultra-stable sub-millimeter-wave/terahertz signal.

Keywords: FM sideband injection locking, Master-Slave injection locking, Millimetre-wave signal generation and Optical heterodyning.

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9340 Small Signal Stability Assessment Employing PSO Based TCSC Controller with Comparison to GA Based Design

Authors: D. Mondal, A. Chakrabarti, A. Sengupta

Abstract:

This paper aims to select the optimal location and setting parameters of TCSC (Thyristor Controlled Series Compensator) controller using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to mitigate small signal oscillations in a multimachine power system. Though Power System Stabilizers (PSSs) are prime choice in this issue, installation of FACTS device has been suggested here in order to achieve appreciable damping of system oscillations. However, performance of any FACTS devices highly depends upon its parameters and suitable location in the power network. In this paper PSO as well as GA based techniques are used separately and compared their performances to investigate this problem. The results of small signal stability analysis have been represented employing eigenvalue as well as time domain response in face of two common power system disturbances e.g., varying load and transmission line outage. It has been revealed that the PSO based TCSC controller is more effective than GA based controller even during critical loading condition.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Small Signal Stability, Thyristor Controlled Series Compensator.

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9339 Spread Spectrum Code Estimation by Genetic Algorithm

Authors: V. R. Asghari, M. Ardebilipour

Abstract:

In the context of spectrum surveillance, a method to recover the code of spread spectrum signal is presented, whereas the receiver has no knowledge of the transmitter-s spreading sequence. The approach is based on a genetic algorithm (GA), which is forced to model the received signal. Genetic algorithms (GAs) are well known for their robustness in solving complex optimization problems. Experimental results show that the method provides a good estimation, even when the signal power is below the noise power.

Keywords: Code estimation, genetic algorithms, spread spectrum.

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