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检索条件"任意字段=Conference on Advanced Signal Processing Algorithms"

共 3487 条记录，以下是381-390 订阅

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An adaptive algorithm for interference cancelling in array processing 6

An adaptive algorithm for interference cancelling in array p...

引用

conference on advanced signal processing algorithms, Architectures, and Implementations VI

作者： Luk, FT Qiao, SZ RENSSELAER POLYTECH INST DEPT COMP SCITROYNY 12180

ISBN: (纸本)0819422347

In array processing, one technique for cancelling interference in the presence of colored noise is the ULLV decomposition of a pair of matrices. The factorization is stable and accurate, and is easy to update when a row is added to either one of the two matrices. In earlier work, we made the assumptions that both matrices must have at least as many rows as columns and that the matrix representing interference must have full column rank. In this paper, we relax the latter restriction and allow the interference matrix to be rank deficient. We present an algorithm for computing the decomposition and two techniques for updating it. The details on updating are quite different from those in the full rank case. © 1996 SPIE. All rights reserved.

关键词： ULLV decomposition matrix updating noise subspace tracking

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ROBUST FRONT-END processing FOR SPEECH RECOGNITION IN NOISY CONDITIONS

ROBUST FRONT-END PROCESSING FOR SPEECH RECOGNITION IN NOISY ...

引用

IEEE International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Das, Biswajit Panda, Ashish TCS Innovat Labs Yantra Pk Thana 400601 Maharashtra India

ISBN: (纸本)9781509041176

In this paper, we investigate the applicability and effectiveness of advanced feature compensation techniques in devising a robust front-end for Automatic Speech Recognition (ASR). First, the Vector Taylor Series (VTS) equations are altered by bringing in the auditory masking factor. The resultant VTS approximation is used to compensate the parameters of a clean speech model and a Minimum Mean Square Error (MMSE) estimate is used to estimate the clean speech features from noisy features. Second, we apply root-compression instead of conventional log-compression to the mel-filter banks energy. Third, we apply a frame selection method to eliminate the noise dominated frames to improve the performance in high noise scenarios. The proposed algorithms are validated on noise corrupted Librispeech and TIMIT speech recognition databases and are shown to provide significant gain in performance.

关键词： Noise robust speech recognition Auditory Masking Vector Taylor series Root Compression Frame Suitability Measure

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Asynchronous 3-Phase Power Measurements

Asynchronous 3-Phase Power Measurements

引用

conference on Precision Electromagnetic Measurements (CPEM)

作者： Timmons, Richard Barczyk, Tom Guildline Instruments Smiths Falls ON Canada

ISBN: (纸本)9781467391344

A new asynchronous, 3-phase/4-channel Power Analyzer for high precision analysis of AC voltage, AC current and power. advanced signal processing algorithms provide precise measurements of single period events (i.e. single period of a wave form) for sinusoidal, non-sinusoidal and quasi-stationary signals. The uncertainty for AC current and power measurements of a single period event are < 75 mu A/A and < 200 mu W/W. The uncertainty of the phase measurement between two single period events (i.e. voltage-to-voltage, current-to-current, and voltage-to-current) is < 50 mu rad. Uncertainties are materially reduced with averaging over multiple periods. This paper describes the architecture and algorithms.

关键词： Asynchronous measurement Frequency-domain analysis Phase measurement Power measurement signal processing algorithms

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Microsystem for signal processing applications

Microsystem for signal processing applications

引用

conference on advanced Sensor Technologies for Nondestructive Evaluation and Structural Health Monitoring

作者： Frankenstein, B Fröhlich, KJ Hentschel, D Reppe, G Fraunhofer Inst Nondestruct Testing Dresden Branch D-01326 Dresden Germany

ISBN: (纸本)0819457515

Acoustic monitoring of technological processes requires methods that eliminate noise as much as possible. Sensor-near signal evaluation can contribute substantially. Frequently, a further necessity exists to integrate the measuring technique into the monitored structure. The solution described contains components for analog preprocessing of acoustic signals, their digitization, algorithms for data reduction, and digital communication. The core component is a digital signal processor (DSP), which performs the basic algorithms necessary for filtering, down sampling, FFT computation and correlation of spectral components particularly effective. A compact, sensor-near signal processing structure was realized. It meets the Match-X standard, which was specified by the German Association for Mechanical and Plant Engineering (VDMA) for development of micro-technical modules, which can be combined to application specific systems. The solution is based on AL(2)O(3) ceramic components including different signal processing modules as ADC, as well as memory and power supply. An arbitrary waveform generator has been developed and combined with a power amplifier for piezoelectric transducers in a special module. A further module interfaces to these transducers. It contains a multi-channel preamplifier, some high-pass and low-pass filters for analog signal processing and an ADC-driver. A Bluetooth communication chip for wireless data transmission and a DiscOnChip module are under construction.

关键词： process monitoring acoustic signal processing microsystem

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Parallel implementation of a face location algorithm on DSP's with SynDEx environment

Parallel implementation of a face location algorithm on DSP'...

引用

conference on advanced signal processing algorithms, Architectures, and Implementations IX

作者： Yang, F Paindavoine, M Abdi, H Univ Burgundy Lab Le2i Fac Sci Mirande F-21011 Dijon France

ISBN: (纸本)0819432938

The aim of our work is to implement a system of automatic face image processing on DSP's : face detection in an image, face recognition and face identification. The first step is to localize the face in an image. Our approach consists to approximate the face oval shape with an ellipse and to compute coordinates of the center of the ellipse. For this purpose, we explore a new version of the Hough transformation : the Fuzzy Generalized Hough transformation. To reduce the computation time, we present also several parallel implementations of the algorithm on a multi-DSP architecture using SynDEx tool which is a programming environment to generate optimized distributed real-time executives. We show that an acceleration of factor 1.7 has been obtained.

关键词： automatic face image processing face location edge detection Hough transformation efficient mapping algorithm and architecture A(3) methodology SynDEx

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GPU Implementations for Fast Factorizations of STAP Covariance Matrices

GPU Implementations for Fast Factorizations of STAP Covarian...

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conference on advanced signal processing algorithms, Architectures, and Implementantions XVIII

作者： Roeder, Michael Davis, Nolan Furtek, Jeremy Braunreiter, Dennis Healy, Dennis Sci Applicat Int Corp 10260 Campus Point Dr San Diego CA 92121 USA DARPA Microsyst Technol Off Arlington VA 22203 USA

ISBN: (纸本)9780819472946

One of the main goals of the STAP-BOY program has been the implementation of a, space-time adaptive processing (STAP) algorithm on graphics processing units (GPUs) with the goal of reducing the processing time. Within the context of GPU implementation, we have further developed algorithms that exploit data redundancy inherent in particular STAP applications. Integration of these algorithms with GPU architecture is of primary importance for fast algorithmic processing times. STAP algorithms involve solving a linear system in which the transformation matrix is a covariance matrix. A standard method involves estimating a covariance matrix from a data matrix, computing its Cholesky factors by one of several methods. and then solving the system by substitution. Some STAP applications have redundancy in successive data matrices from which the covariance matrices are formed. For STAP applications in which a data matrix is updated with the addition of a new data row at the bottom and the elimination of the oldest data in the top of the matrix, a sequence of data matrices have multiple rows in common. Two methods have been developed for exploiting this type of data redundancy when computing Cholesky factors. These two methods are referred to as 1) Fast QR factorizations of successive data matrices 2) Fast Cholesky factorizations of successive covariance matrices. We have developed GPU implementations of these two methods. We show that these two algorithms exhibit reduced computational complexity when compared to benchmark algorithms that do not exploit data, redundancy. More importantly, we show that when these algorithmic improvements are optimized for the GPU architecture, the processing times of a GPU implementation of these matrix factorization algorithms may be greatly improved.

关键词： Covariance cholesky QR factorization GPGPU Space Time Adaptive processing (STAP) block update CUDA thread parallelism block parallelism

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Modulo-addressing utilization in automatic software synthesis for digital signal processors

Modulo-addressing utilization in automatic software synthesi...

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1997 IEEE International conference on Acoustics, Speech, and signal processing (ICASSP 97)

作者： Willems, M Keding, H Zivojnovic, V Meyr, H Aachen Univ of Technology Aachen Germany

ISBN: (纸本)0818679204

Digital signal Processors (DSPs) have become key components for the implementation of digital signal processing systems. With DSPs moving into new application domains and the increasing complexity of modern DSP architectures, efficient programming support receives major interest. Therefore, an optimizing compiler becomes a must for future DSP-architectures. Todays DSP compilers result in significant overheads both in memory consumption and program execution time compared to hand-written assembly code. This is mainly due to an inefficient compiler support of the DSP specific architectural features, such as the modulo-addressing capability which is an enabling feature for a large class of DSP algorithms. Within this paper we analyze why existing compilers fail short in supporting the module-addressing mode and present a compiler concept that allows the efficient utilization of this feature. We describe how an advanced compiler optimization strategy allows a near optimum support of the module-addressing mode, and point out why this concept is favorable to DSP-specific language extensions.

关键词： Program compilers

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Big Data Stream Learning with SAMOA 14

Big Data Stream Learning with SAMOA

引用

14th IEEE International conference on Data Mining (IEEE ICDM)

作者： Bifet, Albert De Francisci Morales, Gianmarco HUAWEI Noahs Ark Lab Hong Kong Hong Kong Peoples R China Yahoo Labs Barcelona Spain

ISBN: (纸本)9781479942749

Big data is flowing into every area of our life, professional and personal. Big data is defined as datasets whose size is beyond the ability of typical software tools to capture, store, manage and analyze, due to the time and memory complexity. Velocity is one of the main properties of big data. In this demo, we present SAMOA (Scalable advanced Massive Online Analysis), an open-source platform for mining big data streams. It provides a collection of distributed streaming algorithms for the most common data mining and machine learning tasks such as classification, clustering, and regression, as well as programming abstractions to develop new algorithms. It features a pluggable architecture that allows it to run on several distributed stream processing engines such as Storm, S4, and Samza. SAMOA is written in Java and is available at http://*** under the Apache Software License version 2.0.

关键词： Big Data data mining learning (artificial intelligence) pattern classification pattern clustering regression analysis Apache Software License version 2.0 Java S4 SAMOA Samza Storm big data stream learning big data stream mining classification task clustering task distributed stream processing engines distributed streaming algorithms machine learning tasks open-source platform pluggable architecture programming abstractions regression task scalable advanced massive online analysis Algorithm design and analysis Big data Data mining Digital signal processing Engines Machine learning algorithms Storms Classification Clustering Data Streams Distributed Systems Machine Learning Regression Toolbox big data storms data mining Samoan Islands Algorithm design and analysis Cluster Analysis Machine learning algorithms Engines tool cases Java Java programming language Distributed Systems Digital signal processing Pattern recognition Regression (Psychology)

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Enhanced Feature Extraction Approaches for Detection of Sound Events 9

Enhanced Feature Extraction Approaches for Detection of Soun...

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IEEE 9th International conference on advanced Computing (IACC)

作者： Surampudi, Naren Srirangan, M. Christopher, Jabez BITS Pilani Dept Elect & Elect Engn Hyderabad Campus Hyderabad Telangana India BITS Pilani Dept Comp Sci & Informat Syst Hyderabad Campus Hyderabad Telangana India

ISBN: (纸本)9781728143927

This work focusses on using digital signal processing techniques to analyze and extract audio features and use them to predict the type of event that might have taken place in an audio signal using supervised machine learning approaches. The performance of five classification approaches using different feature subsets were analysed. Feature subsets include frequencies of the segmental features, frequencies of the supra-segmental features and combination of both. This gives an insight about the relative importance of the feature subsets and also the need for extracting new features from existing features. Features were extracted after the audio signal was filtered using a lowpass Butterworth filter with a cutoff frequency of 1500 Hz;it was inferred that the including features of the difference signals improved the performance of the learning algorithms. The work also includes tuning the parameters of the classification approaches to improve the performance. The observations and inferences of the experimental results can potentially be used for designing robust surveillance systems for rare event detection.

关键词： Audio signal processing Rare event detection Segmental features Supra-segmental features Machine learning

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Time-varying frequencies of a signal

Time-varying frequencies of a signal

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conference on advanced signal processing - algorithms, Architectures, and Implementations VII

作者： Loughlin, PJ Univ. of Pittsburgh (United States)

ISBN: (纸本)0819425842

We consider the definition and interpretation of instantaneous frequency and other time-varying frequencies of a signal, and related concepts of instantaneous amplitude, instantaneous bandwidth and the time-varying spectrum of a signal. A definition for the average frequency at each time is given, and we show that spectrograms and Cohen-Posch time-frequency distributions can yield this result for the first conditional moment in frequency. For some signals this result equals the instantaneous frequency, but generally instantaneous frequency is not the average frequency at each time in the signal. We discuss monocomponent versus multicomponent signals, and give an estimate of the time-varying spectrum given the instantaneous frequencies and bandwidths of the components. We also consider the role of the complex signal in defining instantaneous amplitude, frequency and bandwidth, and ways to obtain a complex signal satisfying certain physical properties, given a real signal (or its time-varying spectrum). Depending upon the physical properties desired (e.g., the instantaneous amplitude of a magnitude-bounded signal should itself be bounded), one obtains different complex representations - and hence different instantaneous amplitudes, frequencies and bandwidths - of the given signal.

关键词： instantaneous frequency, bandwidth Hilbert transform analytic signal time-frequency conditional moments maximum entropy density

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