Search results for: transient signal
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1523

Search results for: transient signal

683 Image Segmentation by Mathematical Morphology: An Approach through Linear, Bilinear and Conformal Transformation

Authors: Dibyendu Ghoshal, Pinaki Pratim Acharjya

Abstract:

Image segmentation process based on mathematical morphology has been studied in the paper. It has been established from the first principles of the morphological process, the entire segmentation is although a nonlinear signal processing task, the constituent wise, the intermediate steps are linear, bilinear and conformal transformation and they give rise to a non linear affect in a cumulative manner.

Keywords: Image segmentation, linear transform, bilinear transform, conformal transform, mathematical morphology.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2155
682 Design of a DCT-based Image Compression with Efficient Enhancement Filter

Authors: Yen-Yu Chen, Pao-Ching Chu, Ya-Ling Tsai

Abstract:

The algorithm represents the DCT coefficients to concentrate signal energy and proposes combination and dictator to eliminate the correlation in the same level subband for encoding the DCT-based images. This work adopts DCT and modifies the SPIHT algorithm to encode DCT coefficients. The proposed algorithm also provides the enhancement function in low bit rate in order to improve the perceptual quality. Experimental results indicate that the proposed technique improves the quality of the reconstructed image in terms of both PSNR and the perceptual results close to JPEG2000 at the same bit rate.

Keywords: JPEG 2000, enhancement filter

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1667
681 A New Spectral-based Approach to Query-by-Humming for MP3 Songs Database

Authors: Leon Fu, Xiangyang Xue

Abstract:

In this paper, we propose a new approach to query-by-humming, focusing on MP3 songs database. Since MP3 songs are much more difficult in melody representation than symbolic performance data, we adopt to extract feature descriptors from the vocal sounds part of the songs. Our approach is based on signal filtering, sub-band spectral processing, MDCT coefficients analysis and peak energy detection by ignorance of the background music as much as possible. Finally, we apply dual dynamic programming algorithm for feature similarity matching. Experiments will show us its online performance in precision and efficiency.

Keywords: DP, MDCT, MP3, QBH.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1760
680 Triple-input Single-output Voltage-mode Multifunction Filter Using Only Two Current Conveyors

Authors: Mehmet Sagbas, Kemal Fidanboylu, M. Can Bayram

Abstract:

A new voltage-mode triple-input single-output multifunction filter using only two current conveyors is presented. The proposed filter which possesses three inputs and single-output can generate all biquadratic filtering functions at the output terminal by selecting different input signal combinations. The validity of the proposed filter is verified through PSPICE simulations.

Keywords: Active Filters, Voltage mode, Current conveyor

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1738
679 Direct Sequence Spread Spectrum Technique with Residue Number System

Authors: M. I. Youssef, A. E. Emam, M. Abd Elghany

Abstract:

In this paper, a residue number arithmetic is used in direct sequence spread spectrum system, this system is evaluated and the bit error probability of this system is compared to that of non residue number system. The effect of channel bandwidth, PN sequences, multipath effect and modulation scheme are studied. A Matlab program is developed to measure the signal-to-noise ratio (SNR), and the bit error probability for the various schemes.

Keywords: Spread Spectrum, Direct sequence, Bit errorprobability and Residue number system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3624
678 0.13-μm CMOS Vector Modulator for Wireless Backhaul System

Authors: J. S. Kim, N. P. Hong

Abstract:

In this paper, a CMOS vector modulator designed for wireless backhaul system based on 802.11ac is presented. A poly phase filter and sign select switches yield two orthogonal signal paths. Two variable gain amplifiers with strongly reduced phase shift of only ±5 ° are used to weight these paths. It has a phase control range of 360 ° and a gain range of -10 dB to 10 dB. The current drawn from a 1.2 V supply amounts 20.4 mA. Using a 0.13 mm technology, the chip die area amounts 1.47x0.75 mm².

Keywords: CMOS, vector modulator, backhaul, 802.11ac.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2241
677 Cost-Optimized SSB Transmitter with High Frequency Stability and Selectivity

Authors: J. P. Dubois

Abstract:

Single side band modulation is a widespread technique in communication with significant impact on communication technologies such as DSL modems and ATSC TV. Its widespread utilization is due to its bandwidth and power saving characteristics. In this paper, we present a new scheme for SSB signal generation which is cost efficient and enjoys superior characteristics in terms of frequency stability, selectivity, and robustness to noise. In the process, we develop novel Hilbert transform properties.

Keywords: Crystal filter, frequency drift, frequency mixing, Hilbert transform, phasing, selectivity, single side band AM.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1394
676 Distance Estimation for Radar Systems Using DS-UWB Signals

Authors: Youngpo Lee, Seokho Yoon

Abstract:

In this paper, we propose a distance estimation scheme for radar systems using direct sequence ultra wideband (DS-UWB) signals. The proposed distance estimation scheme averages out the noise by accumulating the correlator outputs of the radar, and thus, helps the radar to employ a short-length DS-UWB signal reducing the correlation processing time. Numerical results confirm that the proposed distance estimation scheme provides a better estimation performance and a reduced correlation processing time compared with those of the conventional DS-UWB radars.

Keywords: Radar, DS-UWB, distance estimation, correlation accumulation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1999
675 Coupled Multifield Analysis of Piezoelectrically Actuated Microfluidic Device for Transdermal Drug Delivery Applications

Authors: Muhammad Waseem Ashraf, Shahzadi Tayyaba, Nitin Afzulpurkar, Asim Nisar, Adisorn Tuantranont, Erik L J Bohez

Abstract:

In this paper, design, fabrication and coupled multifield analysis of hollow out-of-plane silicon microneedle array with piezoelectrically actuated microfluidic device for transdermal drug delivery (TDD) applications is presented. The fabrication process of silicon microneedle array is first done by series of combined isotropic and anisotropic etching processes using inductively coupled plasma (ICP) etching technology. Then coupled multifield analysis of MEMS based piezoelectrically actuated device with integrated 2×2 silicon microneedle array is presented. To predict the stress distribution and model fluid flow in coupled field analysis, finite element (FE) and computational fluid dynamic (CFD) analysis using ANSYS rather than analytical systems has been performed. Static analysis and transient CFD analysis were performed to predict the fluid flow through the microneedle array. The inlet pressure from 10 kPa to 150 kPa was considered for static CFD analysis. In the lumen region fluid flow rate 3.2946 μL/min is obtained at 150 V for 2×2 microneedle array. In the present study the authors have performed simulation of structural, piezoelectric and CFD analysis on three dimensional model of the piezoelectrically actuated mcirofluidic device integrated with 2×2 microneedle array.

Keywords: Coupled multifield, finite element analysis, hollow silicon microneedle, transdermal drug delivery.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1833
674 Direct Method for Converting FIR Filter with Low Nonzero Tap into IIR Filter

Authors: Jeong Hye Moon, Byung Hoon Kang, PooGyeon Park

Abstract:

In this paper, we proposed the direct method for converting Finite-Impulse Response (FIR) filter with low nonzero tap into Infinite-Impulse Response (IIR) filter using the pre-determined table. The prony method is used by ghost cancellator which is IIR approximation to FIR filter which is better performance than IIR and have much larger calculation difference. The direct method for many ghost combination with low nonzero tap of NTSC(National Television System Committee) TV signal in Korea is described. The proposed method is illustrated with an example.

Keywords: NTSC, Ghost cancellation, FIR, IIR, Prony method.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3126
673 Neuro-Fuzzy System for Equalization Channel Distortion

Authors: Rahib H. Abiyev

Abstract:

In this paper the application of neuro-fuzzy system for equalization of channel distortion is considered. The structure and operation algorithm of neuro-fuzzy equalizer are described. The use of neuro-fuzzy equalizer in digital signal transmission allows to decrease training time of parameters and decrease the complexity of the network. The simulation of neuro-fuzzy equalizer is performed. The obtained result satisfies the efficiency of application of neurofuzzy technology in channel equalization.

Keywords: Neuro-fuzzy system, noise equalization, neuro-fuzzy equalizer, neural system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1618
672 Signal Reconstruction Using Cepstrum of Higher Order Statistics

Authors: Adnan Al-Smadi, Mahmoud Smadi

Abstract:

This paper presents an algorithm for reconstructing phase and magnitude responses of the impulse response when only the output data are available. The system is driven by a zero-mean independent identically distributed (i.i.d) non-Gaussian sequence that is not observed. The additive noise is assumed to be Gaussian. This is an important and essential problem in many practical applications of various science and engineering areas such as biomedical, seismic, and speech processing signals. The method is based on evaluating the bicepstrum of the third-order statistics of the observed output data. Simulations results are presented that demonstrate the performance of this method.

Keywords: Cepstrum, bicepstrum, third order statistics

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2017
671 Computational Fluid Dynamics Simulation Approach for Developing a Powder Dispensing Device

Authors: Rallapalli Revanth, Shivakumar Bhavi, Vijay Kumar Turaga

Abstract:

Dispensing powders manually can be difficult as it requires to gradually pour and check the amount on the scale to be dispensed. Current systems are manual and non-continuous in nature and is user dependent and it is also difficult to control powder dispensation. Recurrent dosing of powdered medicines in precise amounts quickly and accurately has been an all-time challenge. Various powder dispensing mechanisms are being designed to overcome these challenges. Battery operated screw conveyor mechanism is being innovated to overcome above problems faced. These inventions are numerically evaluated at concept development level by employing Computational Fluid Dynamics (CFD) of gas-solids multiphase flow systems. CFD has been very helpful in the development of such devices, saving time and money by reducing the number of prototypes and testing. In this study, powder dispensation from the trocar's end is simulated by using the Dense Discrete Phase Model technique along with Kinetic Theory of Granular Flow. The powder is viewed as a secondary flow in air (DDPM-KTGF). By considering the volume fraction of powder as 50%, the transportation side is done by rotation of the screw conveyor. The performance is calculated for 1 sec time frame in an unsteady computation manner. This methodology will help designers in developing design concepts to improve the dispensation and the effective area within a quick turnaround time frame.

Keywords: Multiphase flow, screw conveyor, transient, DDPM - KTGF.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 346
670 Conventional and PSO Based Approaches for Model Reduction of SISO Discrete Systems

Authors: S. K. Tomar, R. Prasad, S. Panda, C. Ardil

Abstract:

Reduction of Single Input Single Output (SISO) discrete systems into lower order model, using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Modified Cauer Form (MCF) and differentiation are used. In this method the original discrete system is, first, converted into equivalent continuous system by applying bilinear transformation. The denominator of the equivalent continuous system and its reciprocal are differentiated successively, the reduced denominator of the desired order is obtained by combining the differentiated polynomials. The numerator is obtained by matching the quotients of MCF. The reduced continuous system is converted back into discrete system using inverse bilinear transformation. In the evolutionary technique method, Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.

Keywords: Discrete System, Single Input Single Output (SISO), Bilinear Transformation, Reduced Order Model, Modified CauerForm, Polynomial Differentiation, Particle Swarm Optimization, Integral Squared Error.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1930
669 Effect of Shell Dimensions on Buckling Behavior and Entropy Generation of Thin Welded Shells

Authors: Sima Ziaee, Khosro Jafarpur

Abstract:

Among all mechanical joining processes, welding has been employed for its advantage in design flexibility, cost saving, reduced overall weight and enhanced structural performance. However, for structures made of relatively thin components, welding can introduce significant buckling distortion which causes loss of dimensional control, structural integrity and increased fabrication costs. Different parameters can affect buckling behavior of welded thin structures such as, heat input, welding sequence, dimension of structure. In this work, a 3-D thermo elastic-viscoplastic finite element analysis technique is applied to evaluate the effect of shell dimensions on buckling behavior and entropy generation of welded thin shells. Also, in the present work, the approximated longitudinal transient stresses which produced in each time step, is applied to the 3D-eigenvalue analysis to ratify predicted buckling time and corresponding eigenmode. Besides, the possibility of buckling prediction by entropy generation at each time is investigated and it is found that one can predict time of buckling with drawing entropy generation versus out of plane deformation. The results of finite element analysis show that the length, span and thickness of welded thin shells affect the number of local buckling, mode shape of global buckling and post-buckling behavior of welded thin shells.

Keywords: Buckling behavior, Elastic viscoplastic model, Entropy generation, Finite element method, Shell dimensions.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1619
668 Discrete Wavelet Transform Decomposition Level Determination Exploiting Sparseness Measurement

Authors: Lei Lei, Chao Wang, Xin Liu

Abstract:

Discrete wavelet transform (DWT) has been widely adopted in biomedical signal processing for denoising, compression and so on. Choosing a suitable decomposition level (DL) in DWT is of paramount importance to its performance. In this paper, we propose to exploit sparseness of the transformed signals to determine the appropriate DL. Simulation results have shown that the sparseness of transformed signals after DWT increases with the increasing DLs. Additional Monte-Carlo simulation results have verified the effectiveness of sparseness measure in determining the DL.

Keywords: Sparseness, DWT, decomposition level, ECG.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5846
667 Receive and Transmit Array Antenna Spacingand Their Effect on the Performance of SIMO and MIMO Systems by using an RCS Channel Model

Authors: N. Ebrahimi-Tofighi, M. ArdebiliPour, M. Shahabadi

Abstract:

In this paper, the effect of receive and/or transmit antenna spacing on the performance (BER vs. SNR) of multipleantenna systems is determined by using an RCS (Radar Cross Section) channel model. In this physical model, the scatterers existing in the propagation environment are modeled by their RCS so that the correlation of the receive signal complex amplitudes, i.e., both magnitude and phase, can be estimated. The proposed RCS channel model is then compared with classical models.

Keywords: MIMO system, Performance of system, Signalcorrelation, SIMO system, Wireless channel model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1916
666 Hardware Centric Machine Vision for High Precision Center of Gravity Calculation

Authors: Xin Cheng, Benny Thörnberg, Abdul Waheed Malik, Najeem Lawal

Abstract:

We present a hardware oriented method for real-time measurements of object-s position in video. The targeted application area is light spots used as references for robotic navigation. Different algorithms for dynamic thresholding are explored in combination with component labeling and Center Of Gravity (COG) for highest possible precision versus Signal-to-Noise Ratio (SNR). This method was developed with a low hardware cost in focus having only one convolution operation required for preprocessing of data.

Keywords: Dynamic thresholding, segmentation, position measurement, sub-pixel precision, center of gravity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2336
665 Speaker Identification by Atomic Decomposition of Learned Features Using Computational Auditory Scene Analysis Principals in Noisy Environments

Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

Abstract:

Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1545
664 Pattern Recognition of Biological Signals

Authors: Paulo S. Caparelli, Eduardo Costa, Alexsandro S. Soares, Hipolito Barbosa

Abstract:

This paper presents an evolutionary method for designing electronic circuits and numerical methods associated with monitoring systems. The instruments described here have been used in studies of weather and climate changes due to global warming, and also in medical patient supervision. Genetic Programming systems have been used both for designing circuits and sensors, and also for determining sensor parameters. The authors advance the thesis that the software side of such a system should be written in computer languages with a strong mathematical and logic background in order to prevent software obsolescence, and achieve program correctness.

Keywords: Pattern recognition, evolutionary computation, biological signal, functional programming.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1727
663 Study of Adaptive Filtering Algorithms and the Equalization of Radio Mobile Channel

Authors: Said Elkassimi, Said Safi, B. Manaut

Abstract:

This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm.

Keywords: Adaptive filtering second equalizer, LMS, RLS Bran A, Proakis (B) MMSE, ZF.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2107
662 Performance Evaluation of Music and Minimum Norm Eigenvector Algorithms in Resolving Noisy Multiexponential Signals

Authors: Abdussamad U. Jibia, Momoh-Jimoh E. Salami

Abstract:

Eigenvector methods are gaining increasing acceptance in the area of spectrum estimation. This paper presents a successful attempt at testing and evaluating the performance of two of the most popular types of subspace techniques in determining the parameters of multiexponential signals with real decay constants buried in noise. In particular, MUSIC (Multiple Signal Classification) and minimum-norm techniques are examined. It is shown that these methods perform almost equally well on multiexponential signals with MUSIC displaying better defined peaks.

Keywords: Eigenvector, minimum norm, multiexponential, subspace.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1721
661 Development of a Feedback Control System for a Lab-Scale Biomass Combustion System Using Programmable Logic Controller

Authors: Samuel O. Alamu, Seong W. Lee, Blaise Kalmia, Marc J. Louise Caballes, Xuejun Qian

Abstract:

The application of combustion technologies for thermal conversion of biomass and solid wastes to energy has been a major solution to the effective handling of wastes over a long period of time. Lab-scale biomass combustion systems have been observed to be economically viable and socially acceptable, but major concerns are the environmental impacts of the process and deviation of temperature distribution within the combustion chamber. Both high and low combustion chamber temperature may affect the overall combustion efficiency and gaseous emissions. Therefore, there is an urgent need to develop a control system which measures the deviations of chamber temperature from set target values, sends these deviations (which generates disturbances in the system) in the form of feedback signal (as input), and control operating conditions for correcting the errors. In this research study, major components of the feedback control system were determined, assembled, and tested. In addition, control algorithms were developed to actuate operating conditions (e.g., air velocity, fuel feeding rate) using ladder logic functions embedded in the Programmable Logic Controller (PLC). The developed control algorithm having chamber temperature as a feedback signal is integrated into the lab-scale swirling fluidized bed combustor (SFBC) to investigate the temperature distribution at different heights of the combustion chamber based on various operating conditions. The air blower rates and the fuel feeding rates obtained from automatic control operations were correlated with manual inputs. There was no observable difference in the correlated results, thus indicating that the written PLC program functions were adequate in designing the experimental study of the lab-scale SFBC. The experimental results were analyzed to study the effect of air velocity operating at 222-273 ft/min and fuel feeding rate of 60-90 rpm on the chamber temperature. The developed temperature-based feedback control system was shown to be adequate in controlling the airflow and the fuel feeding rate for the overall biomass combustion process as it helps to minimize the steady-state error.

Keywords: Air flow, biomass combustion, feedback control system, fuel feeding, ladder logic, programmable logic controller, temperature.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 555
660 Epileptic Seizure Prediction by Exploiting Signal Transitions Phenomena

Authors: Mohammad Zavid Parvez, Manoranjan Paul

Abstract:

A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/ deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.

Keywords: Epilepsy, Seizure, Phase Correlation, Fluctuation, Deviation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2449
659 A Virtual Simulation Environment for a Design and Verification of a GPGPU

Authors: Kwang Y. Lee, Tae R. Park, Jae C. Kwak, Yong S. Koo

Abstract:

When a small H/W IP is designed, we can develop an appropriate verification environment by observing the simulated signal waves, or using the serial test vectors for the fixed output. In the case of design and verification of a massive parallel processor with multiple IPs, it-s difficult to make a verification system with existing common verification environment, and to verify each partial IP. A TestDrive verification environment can build easy and reliable verification system that can produce highly intuitive results by applying Modelsim and SystemVerilog-s DPI. It shows many advantages, for example a high-level design of a GPGPU processor design can be migrate to FPGA board immediately.

Keywords: Virtual Simulation, Verification, IP Design, GPGPU

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1643
658 Simulation of Utility Accrual Scheduling and Recovery Algorithm in Multiprocessor Environment

Authors: A. Idawaty, O. Mohamed, A. Z. Zuriati

Abstract:

This paper presents the development of an event based Discrete Event Simulation (DES) for a recovery algorithm known Backward Recovery Global Preemptive Utility Accrual Scheduling (BR_GPUAS). This algorithm implements the Backward Recovery (BR) mechanism as a fault recovery solution under the existing Time/Utility Function/ Utility Accrual (TUF/UA) scheduling domain for multiprocessor environment. The BR mechanism attempts to take the faulty tasks back to its initial safe state and then proceeds to re-execute the affected section of the faulty tasks to enable recovery. Considering that faults may occur in the components of any system; a fault tolerance system that can nullify the erroneous effect is necessary to be developed. Current TUF/UA scheduling algorithm uses the abortion recovery mechanism and it simply aborts the erroneous task as their fault recovery solution. None of the existing algorithm in TUF/UA scheduling domain in multiprocessor scheduling environment have considered the transient fault and implement the BR mechanism as a fault recovery mechanism to nullify the erroneous effect and solve the recovery problem in this domain. The developed BR_GPUAS simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. Simulation results revealed that BR_GPUAS algorithm can saved almost 20-30% of the accumulated utilities making it reliable and efficient for the real-time application in the multiprocessor scheduling environment.

Keywords: Time Utility Function/ Utility Accrual (TUF/UA) scheduling, Real-time system (RTS), Backward Recovery, Multiprocessor, Discrete Event Simulation (DES).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 949
657 The Multi-Layered Perceptrons Neural Networks for the Prediction of Daily Solar Radiation

Authors: Radouane Iqdour, Abdelouhab Zeroual

Abstract:

The Multi-Layered Perceptron (MLP) Neural networks have been very successful in a number of signal processing applications. In this work we have studied the possibilities and the met difficulties in the application of the MLP neural networks for the prediction of daily solar radiation data. We have used the Polack-Ribière algorithm for training the neural networks. A comparison, in term of the statistical indicators, with a linear model most used in literature, is also performed, and the obtained results show that the neural networks are more efficient and gave the best results.

Keywords: Daily solar radiation, Prediction, MLP neural networks, linear model

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1307
656 Applications of Stable Distributions in Time Series Analysis, Computer Sciences and Financial Markets

Authors: Mohammad Ali Baradaran Ghahfarokhi, Parvin Baradaran Ghahfarokhi

Abstract:

In this paper, first we introduce the stable distribution, stable process and theirs characteristics. The a -stable distribution family has received great interest in the last decade due to its success in modeling data, which are too impulsive to be accommodated by the Gaussian distribution. In the second part, we propose major applications of alpha stable distribution in telecommunication, computer science such as network delays and signal processing and financial markets. At the end, we focus on using stable distribution to estimate measure of risk in stock markets and show simulated data with statistical softwares.

Keywords: stable distribution, SaS, infinite variance, heavy tail networks, VaR.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2036
655 Optimum Cascaded Design for Speech Enhancement Using Kalman Filter

Authors: T. Kishore Kumar

Abstract:

Speech enhancement is the process of eliminating noise and increasing the quality of a speech signal, which is contaminated with other kinds of distortions. This paper is on developing an optimum cascaded system for speech enhancement. This aim is attained without diminishing any relevant speech information and without much computational and time complexity. LMS algorithm, Spectral Subtraction and Kalman filter have been deployed as the main de-noising algorithms in this work. Since these algorithms suffer from respective shortcomings, this work has been undertaken to design cascaded systems in different combinations and the evaluation of such cascades by qualitative (listening) and quantitative (SNR) tests.

Keywords: LMS, Kalman filter, Speech Enhancement and Spectral Subtraction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1717
654 Comparison of Frequency Estimation Methods for Reflected Signals in Mobile Platforms

Authors: Kathrin Reinhold

Abstract:

Precise frequency estimation methods for pulseshaped echoes are a prerequisite to determine the relative velocity between sensor and reflector. Signal frequencies are analysed using three different methods: Fourier Transform, Chirp ZTransform and the MUSIC algorithm. Simulations of echoes are performed varying both the noise level and the number of reflecting points. The superposition of echoes with a random initial phase is found to influence the precision of frequency estimation severely for FFT and MUSIC. The standard deviation of the frequency using FFT is larger than for MUSIC. However, MUSIC is more noise-sensitive. The distorting effect of superpositions is less pronounced in experimental data.

Keywords: Frequency estimation, pulse-echo-method, superposition, echoes.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1149