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A novel signal detection technique based on generalized scale transforms - art. no. 63130Y

A novel signal detection technique based on generalized scal...

引用

Conference on advanced signal processing algorithms, architectures, and implementations xvi

作者： Nickel, Robert M. Penn State Univ Dept Elect Engn University Pk PA 16802 USA

ISBN: (纸本)0819463922

We are presenting an extension to the classic multiple signal classification method (MUSIC) developed by Schmidt and Bienvenu in 1979.(1) While the classic MUSIC algorithm is limited to the detection of constant frequency sinusoids in white noise, the proposed new method is capable of detecting signals with a continuously varying instantaneous frequency. The method is based on the development of a discrete-time version of the generalized scale transform (GST) which was introduced by Nickel and Williams in 1999.(2) As a byproduct we obtain techniques for discrete-time warp-shift invariant filtering which can be used in addition to the signal detection to separate signals with different instantaneous frequency contours.

关键词： warping functions sampling theory generalized scale transform signal detection multiple signal classification (MUSIC)

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Application of time-frequency analysis methods to speaker verification

Application of time-frequency analysis methods to speaker ve...

引用

Conference on advanced signal processing algorithms, architectures, and implementations xvi

作者： Williams, W. J. Bossemeyer, R. W. Quantum Signal LLC Ann Arbor MI 48176 USA Univ Michigan EECS Ann Arbor MI 48109 USA Speech Technol Appl Res Inc St Charles IL USA

ISBN: (纸本)0819463922

Time-Frequency Analysis has previously been successfully applied to characterize and quantify a variety of acoustic signals, including marine mammal sounds. In this research, Time-Frequency analysis is applied to human speech signals in an effort to reveal signal structure salient to the biometric speaker verification challenge. Prior approaches to speaker verification have relied upon signal processing analysis such as linear prediction or weighted Cepstrum spectral representations of segments of speech and classification techniques based on stochastic pattern matching. The authors believe that the classification of identity of a speaker based on time-frequency representation of short time events occurring in speech could have substantial advantages. Using these ideas, a speaker verification algorithm was developed(1) and has been refined over the past several years. In this presentation, the authors describe the testing of the algorithm using a large speech database, the results obtained, and recommendations for further improvements.

关键词： time-frequency speaker verification multimodal biometrics homeland security pattern recognition

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An efficient high-resolution time-frequency representation

An efficient high-resolution time-frequency representation

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Conference on advanced signal processing algorithms, architectures, and implementations xvi

作者： Nelson, D. J. Smith, D. C. US Dept Def R61 Ft George G Meade MD 20755 USA

ISBN: (纸本)0819463922

We address the problem of efficient resolution, detection and estimation of weak tones in a potentially massive amount of data. Our goal is to produce a relatively small reduced data set characterizing the signals in the environment in time and frequency. The requirements for this problem are that the process must be computationally efficient, high gain and able to resolve signals and efficiently compress the signal information into a form that may be easily displayed and further processed. We base our process on the cross spectral representation we have previously applied to other problems. In selecting this method, we have considered other representations and estimation methods such as the Wigner distribution and Welch's method. We compare our method to these methods. The spectral estimation method we propose is a variation of Welch's method and the cross-power spectral (CPS) estimator which was first applied to signal estimation and detection in the mid 1980's. The CPS algorithm and the method we present here are based on the principles first described by Kodera et at. now frequently called the reassignment principle.

关键词： signal detection signal estimation transient signals time-frequency representations

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VHDL token-based performance modeling for 2D and 3D infrared search and track processing

VHDL token-based performance modeling for 2D and 3D infrared...

引用

SPIE Conference on advanced signal processing algorithms, architectures, and implementations VIII

作者： Pauer, EK Pettigrew, MN Myers, CS Madisetti, VK Signal Proc Ctr Nashua NH 03061 USA

ISBN: (纸本)0819429163

This study develops and evaluates a new VHDL-based performance modeling capability for multiprocessor systems.* The framework for this methodology involved modeling the following system aspects: processor characterization, task modeling, network characterization, and data set size. Initially, all aspects are specified at an abstract) level, and eventually become specified at a detailed level through the process of verification and refinement of design assumptions. Processor characterization involves modeling the processor's speed, instruction set, and memory hierarchy. Task modeling is concerned with the execution time and instruction mix of software tasks within the system. Network characterization models bus protocols, topology, and bandwidths. Data set size refers to how much data is represented by the tokens used in the models. In this study, we applied and evaluated this methodology using both two-dimensional (2D) and three-dimensional (3D) infrared search and track (IRST) algorithms. Two different candidate processors were investigated: IBM PowerPC 604 and Texas Instruments TMS320C80. For the 2D IRST algorithm, the abstract and detailed performance modeling results were obtained far both processors using partitioned data and pipelined algorithmic approaches. For the 3D IRST algorithm, abstract performance models for pipelined and parallelized implementations on the PowerPC were developed. These models examined the feasibility of the implementations, the potential risk areas, and laid the groundwork for detailed performance modeling.

关键词： performance modeling VHDL IRST architectures simulation

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A total variation wavelet inpainting model with multilevel fitting parameters

A total variation wavelet inpainting model with multilevel f...

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Conference on advanced signal processing algorithms, architectures, and implementations xvi

作者： Chan, Tony F. Shen, Jianhong Zhou, Hao-Min Univ Calif Los Angeles Dept Math Los Angeles CA 90095 USA Univ Minnesota Dept Math Minneapolis MN 55455 USA Georgia Inst Technol Sch Math Atlanta GA 30332 USA

ISBN: (纸本)0819463922

In [14], we have proposed two total variation (TV) minimization wavelet models for the problem of filling in missing or damaged wavelet coefficients due to lossy image transmission or communication. The proposed models can have effective and automatic control over geometric features of the inpainted images including sharp edges, even in the presence of substantial loss of wavelet coefficients, including in the low frequencies. In this paper, we investigate a modification of the model for noisy images to further improve the recovery properties by using multi-level parameters in the fitting term. Some new numerical examples are also shown to illustrate the effectiveness of the recovery.

关键词： Wavelets Image compression Image restoration Image processing Image quality Wavelet transforms Automatic control Cameras Image transmission Mathematics

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VLSI implementations OF NUMBER THEORETIC CONCEPTS WITH APPLICATIONS IN signal-processing

VLSI IMPLEMENTATIONS OF NUMBER THEORETIC CONCEPTS WITH APPLI...

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CONF ON advanced signal processing algorithms, architectures, AND implementations 3

作者： WIGLEY, NM JULLIEN, GA Univ. of Windsor (Canada)

ISBN: (纸本)081940943X

This paper explores novel techniques involving number theoretic concepts to perform real-time digital signal processing for high bandwidth data stream applications in digital signal processing. Often the arithmetic manipulations are simple in form (cascades of additions and multiplications in a well defined structure) but the numbers of operations that have to be computed every second can be large. This paper discusses ways in which new number theoretic mapping techniques can be used to perform DSP operations by both reducing the amount of hardware involved in the circuitry and by allowing the construction of very benign architectures down to the individual cells. Such architectures can be used in aggressive VLSI/ULSI implementations. We restrict ourselves to the computation of linear filter and transform algorithms, with the inner product form, which probably account for the vast majority of digital signal processing functions implemented commercially.

关键词： Digital signal processing Switching Radon Binary data Transistors Logic Very large scale integration Clocks CRTs signal processing

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FPGA-based artificial neural network using CORDIC modules

FPGA-based artificial neural network using CORDIC modules

引用

Conference on advanced signal processing algorithms, architectures, and implementations xvi

作者： Liddicoat, Albert A. Slivovsky, Lynne A. McLenegan, Tim Heyer, Don Calif Polytech State Univ San Luis Obispo Dept Elect Engn San Luis Obispo CA 93407 USA

ISBN: (纸本)0819463922

Artificial neural networks have been used in applications that require complex procedural algorithms and in systems which lack an analytical mathematic model. By designing a large network of computing nodes based on the artificial neuron model, new solutions can be developed for computational problems in fields such as image processing and speech recognition. Neural networks are inherently parallel since each neuron, or node, acts as an autonomous computational element. Artificial neural networks use a mathematical model for each node that processes information from other nodes in the same region. The information processing entails computing a weighted average computation followed by a nonlinear mathematical transformation. Some typical artificial neural network applications use the exponential function or trigonometric functions for the nonlinear transformation. Various simple artificial neural networks have been implemented using a processor to compute the output for each node sequentially. This approach uses sequential processing and does not take advantage of the parallelism of a complex artificial neural network. In this work a hardware-based approach is investigated for artificial neural network applications. A Field Programmable Gate Arrays (FPGAs) is used to implement an artificial neuron using hardware multipliers, adders and CORDIC functional units. In order to create a large scale artificial neural network, area efficient hardware units such as CORDIC units are needed. High performance and low cost bit serial CORDIC implementations are presented. Finally, the FPGA resources and the performance of a hardware-based artificial neuron are presented.

关键词： computer arithmetic field programmable gate arrays (FPGAs) higher-level functions reconfigurable computing digital signal processing and artificial neural networks

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TOMOGRAPHIC TECHNIQUES IN IMAGE AND signal-processing

TOMOGRAPHIC TECHNIQUES IN IMAGE AND SIGNAL-PROCESSING

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CONF ON advanced signal-processing algorithms, architectures, AND implementations

作者： SNYDER, DL Washington Univ. (United States)

An iterative solution is given for solving deblurring problems having nonnegativity constraints through the use of methods motivated by tomographic imaging.

ISBN: (纸本)0819404098

An iterative solution is given for solving deblurring problems having nonnegativity constraints through the use of methods motivated by tomographic imaging.

关键词： Tomography Expectation maximization algorithms signal processing Image processing Reconstruction algorithms Imaging systems Detection and tracking algorithms Sensors Stochastic processes Image filtering

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Time-varying noise

Time-varying noise

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Conference on advanced signal processing algorithms, architectures, and implementations XIV

作者： Galleani, L Cohen, L CUNY New York NY 10021 USA

We obtain the exact Wigner spectrum for non-white Gaussian noise. As a special case the Wigner spectrum for the Wiener process is obtained.

ISBN: (纸本)0819454974

We obtain the exact Wigner spectrum for non-white Gaussian noise. As a special case the Wigner spectrum for the Wiener process is obtained.

关键词： signal processing

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SYSTOLIC ADAPTIVE BEAMFORMING - FROM THEORY TO PRACTICE

SYSTOLIC ADAPTIVE BEAMFORMING - FROM THEORY TO PRACTICE

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CONF ON advanced signal processing algorithms, architectures, AND implementations 2

作者： HARGRAVE, P BNR Europe Ltd. (United Kingdom)

In this paper we describe aspects of an ongoing program of work aimed at the practical realization of systolic array structures to implement digital adaptive beam-forming algorithms.

ISBN: (纸本)0819406945

In this paper we describe aspects of an ongoing program of work aimed at the practical realization of systolic array structures to implement digital adaptive beam-forming algorithms.

关键词： signal processing Acoustics Antennas Algorithm development Phased arrays Prototyping Digital electronics Array processing Data processing Sensors

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