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检索条件"主题词=linear predictive coding"

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Speech-like Analysis of Snore Signals for the Detection of Obstructive Sleep Apnea

Speech-like Analysis of Snore Signals for the Detection of O...

引用

International Conference on Biomedical and Pharmaceutical Engineering, ICBPE

作者： Andrew K. Ng T.S. Koh Eugene Baey K. Puvanendran Centre for Modeling and Control of Complex Systems School of Electrical and Electronic Engineering Nanyang Technological University Singapore Respironics Incorporated Sleep Disorders Unit Singapore General Hospital Singapore

Correlation between snoring and obstructive sleep apnea (OSA) has been studied over the past years using techniques such as sound intensity computation, power spectrum estimation, counting of snores, and more recently, pitch and jitter analysis. Although these studies have ascertained the relationship between snoring and OSA, they gave mixed outcomes in diagnosing OSA. In this paper, snore signals are analyzed using linear predictive coding (LPC), which is a powerful speech analytic tool. The noisy snore signals were first preprocessed using a Modified Normalized Least-Mean-Square (MNLMS) adaptive filter for noise cancellation, followed by the extraction of formant structures from the denoised snore signals to discriminate between benign and apneic snores. This initial study demonstrates that the formant structures of snore signals contain useful information for OSA detection, and suggests the feasibility of using snore signal analysis as a noninvasive and inexpensive diagnostic tool for mass screening of OSA.

关键词： Sleep apnea Signal analysis Speech analysis linear predictive coding Noise cancellation Spectral analysis Jitter Speech coding Acoustic noise Adaptive filters

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Low Power Cache Architecture

Low Power Cache Architecture

引用

IEEE International Workshop on System-on-Chip for Real-Time Applications

作者： Mouna Nakkar Nadia Ahmed Electrical/Electronics and Computer Engineering University of Sharjah Sharjah UAE

ISBN: (纸本)1424408989

Power consumption is becoming a pressing issue in microprocessor design. Caches usually consume large part of the total power consumption of the chip. This paper introduces a novel low power cache architecture which is based on separating the in-coming cache data. Data is separated in two different banks: bank1 that mostly contains 1s data and bank0 that mostly contains 0s data. This separation in part reduces transistor switching activity inside the on-chip cache and hence dynamic power consumption. This papers shows up to 35% reduction for small sized cache of 1K and 9% for typical sized caches of 32K

关键词： Energy consumption linear predictive coding System-on-a-chip Real time systems Computer architecture Microprocessors Application software Power engineering computing Time sharing computer systems Design engineering

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Approach Based on ICA and SVM to Identify Field Mixed Acoustic Targets

Approach Based on ICA and SVM to Identify Field Mixed Acoust...

引用

IEEE International Conference on Radar

作者： Fugui Huang Gong Chen Xiongwei Zhang Department of Electronic Information Engineering ICE of PLAUST Nanjing China

With ICA to realize the blind separation from mixed acoustic targets, an identification method based on SVM is proposed through extracting LPC feature. SVM is employed to compute the output score and k-means algorithm is used as cluster LPC coefficients. Finally targets are identified by hybrid model. Simulation indicates that this method is effective in mixed acoustic targets identification system

关键词： Independent component analysis Support vector machines linear predictive coding Feature extraction Acoustic noise Clustering algorithms Helicopters Degradation Acoustic waves Signal analysis

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Variable Frame Size for Vector Quantization

Variable Frame Size for Vector Quantization

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： C. Moreno F. Labeau Department of Electrical & Computer Engineering McGill University Montreal Canada

Vector quantization (VQ) is a lossy data compression technique that is often applied in the field of speech communications. When applying VQ to speech signals, usually combined with some for of linear prediction coding (LPC), the input signal is divided into frames of a given length. Each frame is then processed and quantized using VQ. A typical assumption is the fact that the frame size is fixed. In this study, we propose a modification to this technique that allows for variable size frames, providing an additional degree of freedom for the optimization of the encoding process. The results show that this technique effectively improves the quality of the encoded signal at a given bit rate, even if the improvement is not dramatic

关键词： Vector quantization Encoding Data compression linear predictive coding Bit rate Oral communication Speech coding Data engineering Signal processing Entropy

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New Technique to Reduce Bit Rate of LPC-10 Speech Coder

New Technique to Reduce Bit Rate of LPC-10 Speech Coder

引用

IEEE Region 10 International Conference TENCON

作者： J. Srinonchat Signal and System Research Laboratory Electronics and Telecommunication Engineering Department Rajamangala University of Technology Pathum Thani Thailand

There are different optimisation criteria in the design of speech compression algorithms and in development speech coding system. linear predictive coder (LPC) parameters are widely used in a various speech coding method. Line spectrum pairs (LSP), as alternate representation of LPC presents some useful properties for quantisation and transmission. This work investigates and proposes an efficient new technique and parameters to reduce the bit rate while maintain the reconstruct speech as the original speech in the LPC-10 speech code. The new technique is based on the LSP parameters and vector quantisation technique. The results of this experiments show that this technique can reduce the bit rate by around 2-66% and also provides the excellent formant frequency similar to the original speech

关键词： Bit rate Speech coding linear predictive coding Speech synthesis Equations predictive models Transfer functions Vector quantization Frequency Tin

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Automating Power Quality Disturbance Analysis Using the IPQDA Software Tool

Automating Power Quality Disturbance Analysis Using the IPQD...

引用

Student Conference on Research and Development (SCOReD)

作者： Hasniaty Azah Mohamed Aini Hussain Department of Electrical Electronic and Systems Engineering Faculty of Engineering Universiti Kebangsaan Malaysia Bangi Selangor Darul Ehsan Malaysia

Automatic recognition of power quality (PQ) disturbances with regards to PQ monitoring is highly desired by both utilities and commercial customers. This paper presents the development of the intelligent power quality data analysis (IPQDA) software tool for the purpose of automatic disturbance classification. The main capabilities of the software include analysis of disturbance waveforms, classification of various types of PQ disturbances and notification of a disturbance. An important feature of the software is that it can automatically send email or short messaging notifications upon identification of a disturbance so as to alert a system operator of a disturbance. In the software development, the two main tasks performed are feature extraction and automatic disturbance classification. Initially, disturbance waveforms are analyzed using the signal processing techniques such as the linear predictive coding and the fast Fourier transform techniques. The feature extraction process of PQ disturbance waveforms is to project a PQ signal into a low-dimension time frequency representation which is deliberately design for maximizing the separability between classes. The unique features of the PQ disturbances are extracted and used in the intelligent analysis too. The second task is to automatically classify the PQ disturbances into different categories of disturbances based on the features extracted from the processed waveform signal. The classification task was performed by developing a rule based expert system in Visual Basic. To verify the accuracy of the developed software tool, it has been tested with 500 recorded voltage disturbance signals which are obtained from PQ monitoring at various sites. In this paper, the focus is to highlight on the accuracy of the software in automatically classifying the distinct categories of PQ disturbance types such as voltage sag, swell, notching and transient. In addition, a statistical analysis has also been performed to further val

关键词： Power quality Software tools Feature extraction Signal processing Voltage fluctuations Computerized monitoring Data analysis Programming Signal analysis linear predictive coding

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Non-linear Predictors based on the Functionally Expanded Neural Networks for Speech Feature Extraction

Non-Linear Predictors based on the Functionally Expanded Neu...

引用

IEEE International Conference on Engineering of Intelligent Systems, ICEIS

作者： M. Chetouani A. Hussain B. Gas J.-L. Zarader Department of Computing Science and Mathematics University of Stirling UK Université Paris Pierre et Marie Curie Paris France

In this paper we focus on the design of the feature extractor stage of the speech recognition system which aims to compute optimal vectors for the next phoneme classification stage. We propose a new non-linear feature extraction method based on the linear-in-parameters functionally expanded neural network (FENN) model. The main idea is to design an improved and flexible feature extractor which can effectively account for some of the significant non-linear phenomena usually observed in the speech production process. The effectiveness of the proposed method is assessed on phoneme classification tasks. Specifically, we evaluate the performances on the telephone quality NTIMIT database, focusing the investigations on highly confusable phonemes such as front vowels: /ih/, /ey/, /eh/, /ae/. The results are compared with other widely used coding methods namely, the linear predictive coding (LPC) and the Mel frequency cepstral coding (MFCC). The experiments show a relative improvement in the rates through the use of our proposed non-linear feature extractor technique

关键词： Neural networks Feature extraction Mel frequency cepstral coefficient linear predictive coding Speech recognition Speech processing Performance evaluation Telephony Spatial databases Cepstral analysis

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Design of Low power & Reliable Networks on Chip through joint crosstalk avoidance and forward error correction coding

Design of Low power & Reliable Networks on Chip through join...

引用

IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems

作者： Partha Pratim Pande Amlan Ganguly Brett Feero Benjamin Belzer Cristian Grecu School of Electrical Engineering & Computer Science Washington State University Pullman WA USA Department of Electrical & Computer Engineering University of British Columbia BC Canada

ISBN: (纸本)9780769527062;076952706X

With the ever-increasing degrees of integration, design of communication architectures for big systems on chip (SoCs) is a challenge. The communication requirements of these large multi processor SoCs (MP-SoCs) are convened by the emerging network-on-a-chip (NoC) paradigm. To become a viable alternative IC design methodology, the NoC paradigm must address system-level reliability issues, which are among the dominant concerns for SoC design. The basic operations of NoCs are governed by on-chip packet switched networks. On the other hand, incorporation of different coding schemes in SoC design is being investigated as a means to increase system reliability. As NoCs are built on packet-switching, it is very natural to modify the data packets by adding extra bits of coded information to protect against any transient malfunction. By incorporating joint crosstalk avoidance coding (CAC) and forward error correction (FEC) schemes in the NoC data stream we are able to enhance the system reliability and at the same time reduce communication energy

关键词： Network-on-a-chip Crosstalk Forward error correction Energy dissipation Wire Reliability Switches Communication switching Codecs linear predictive coding

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RD Optimal Temporal Noise Shaping for Transform Audio coding

RD Optimal Temporal Noise Shaping for Transform Audio Coding

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： O.A. Niamut R. Heusdens Department of Mediamatics Delft University of Technnology Delft Netherlands

In this article we investigate rate-distortion optimal temporal noise shaping for transform audio coding. Temporal noise shaping, or TNS, is a technique for reshaping the quantization noise in the time domain through open-loop linear predictive coding of frequency domain coefficients. Traditionally, a selection mechanism based on prediction gain is employed to determine whether it is advantageous to apply TNS or not. Although this method is effective for reducing coding artifacts in transient and speech signals, critical adjustment of the prediction gain threshold is necessary to avoid excessive bit rate demands. We propose the use of TNS in a rate-distortion optimization framework. Within this framework a jointly optimal selection of the prediction filter order and the quantizer for coding the coefficients can be made, such that the perceptual distortion is minimized for a given target rate. Experimental results for an MDCT-based audio coding system are presented and it is shown that TNS within an RD optimization framework outperforms the existing TNS method

关键词： Noise shaping Audio coding Rate-distortion Quantization linear predictive coding Frequency domain analysis Speech coding Bit rate Filters Optimization methods

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Analysis of the Behaviour of Genetic Algorithm Applied in Optimization of Electrical System Design for Offshore Wind Farms

Analysis of the Behaviour of Genetic Algorithm Applied in Op...

引用

Annual Conference of Industrial Electronics Society

作者： Menghua Zhao Zhe Chen Jesper Hjerrild Institute of Energy Technology University of Aalborg Aalborg Denmark Elsam Engineering A S Fredericia Denmark

Genetic algorithms (GA) have been applied in many fields to solve multivariable, non linear optimization problems. There are lots of different GA techniques which are used to improve the performance of the algorithm. In this paper, the implementation of GA in optimization of electrical system design for offshore wind farms is proposed and several different GA techniques are investigated. The main problems of GA implementation in this field are addressed and the suitable GA techniques are proposed. The GA method is applied to a real offshore wind farm and the results are evaluated. It is concluded that the genetic algorithm is suitable for the optimization of offshore wind farm layout design as long as proper GA techniques are employed

关键词： Algorithm design and analysis Genetic algorithms Design optimization System analysis and design Wind farms Wind turbines linear predictive coding Cost function Power generation economics Environmental economics

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