We generalize the concept of the autocorrelation function to arbitrary physical variables and show how it can be used to define a local autocorrelation function. Using the local autocorrelation function we develop a n...
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ISBN:
(纸本)0819429163
We generalize the concept of the autocorrelation function to arbitrary physical variables and show how it can be used to define a local autocorrelation function. Using the local autocorrelation function we develop a new method to generate densities for arbitrary physical quantities. In addition, we show that the generalized autocorrelation function can be used to characterize functions with respect to a physical property.
This paper presents an application of formal mathematics to create a high performance, low power architecture for time-frequency and time-scale computations implemented in asynchronous circuit technology that achieves...
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ISBN:
(纸本)0819429163
This paper presents an application of formal mathematics to create a high performance, low power architecture for time-frequency and time-scale computations implemented in asynchronous circuit technology that achieves significant power reductions and performance enhancements over more traditional approaches. Utilizing a combination of concepts from multirate signalprocessing and asynchronous circuit design, a case study is presented dealing with a new architecture for the fast Fourier transform, an algorithm that requires globally shared results. Then, the generalized distributive law is presented as an important paradigm for advanced asynchronous hardware design.
In this report, we propose combining the Total variation denoising method with the high loss wavelet compression for high noise level images. Numerical experiments show that Tv-denoising can bring more wavelet coeffic...
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ISBN:
(纸本)0819429163
In this report, we propose combining the Total variation denoising method with the high loss wavelet compression for high noise level images. Numerical experiments show that Tv-denoising can bring more wavelet coefficients closer to zero thereby making the compression more efficient while the salient features (edges) of the images can still be retained.
The objective of this paper is to demonstrate how, in a few seconds, a relatively simple ECG monitor, PC and advancedsignalprocessingalgorithms could pinpoint microvolts- late potentials- with a very low (-30 dB an...
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ISBN:
(纸本)0819429163
The objective of this paper is to demonstrate how, in a few seconds, a relatively simple ECG monitor, PC and advancedsignalprocessingalgorithms could pinpoint microvolts- late potentials- with a very low (-30 dB and below) signal-to-noise ratio in a non-stationary-colored non-Gaussian distributed noise. Late potentials (LP's) result from an infarct zone in the heart and is used as an indicator in identifying patients prone to ventricular tachycardia (vT) which, if left untreated, leads to ventricular fibrillation. We will characterize recorded ECG data obtained from the standard three vector electrodes during exercise in terms of their higher-order statistical features. Essentially we use adaptive LMS- and Kalman-based second- and third-order volterra filters to model the non-linear low-frequency P and T waves and motion artifacts which might overlap with the QRS complex and lead to false positive QRS detection. We will illustrate the effectiveness of this new approach by mapping out bispectral regions with a strong bicoherence manifestation and showing their corresponding temporal/spatial origins. Furthermore, we will present a few examples of our own application of these non-invasive techniques to illustrate what we see as their promise for analysis of heart abnormality.
We briefly review the signalprocessing architecture of a wireless MEM sensor system for source detection, signal enhancement, localization, and identification. A blind beamformer using only the measured data of rando...
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ISBN:
(纸本)0819429163
We briefly review the signalprocessing architecture of a wireless MEM sensor system for source detection, signal enhancement, localization, and identification. A blind beamformer using only the measured data of randomly distributed sensors to form a sample correlation matrix is proposed. The maximum power collection criterion is used to obtain array weights from the dominant eigenvector of the sample correlation matrix. An effective blind beamforming estimation of the time delays of the dominant source is demonstrated. Source localization based on a novel least-squares method for time delay estimation is also given. Array system performance based on analysis, simulation, and measured acoustical/seismic sensor data is presented. Applications of such a system to multimedia, intrusion detection, and surveillance are briefly discussed.
Scheduling and retiming are important techniques used in the design of hardware and software implementations of digital signalprocessingalgorithms. In this paper, techniques are developed for generating all scheduli...
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Scheduling and retiming are important techniques used in the design of hardware and software implementations of digital signalprocessingalgorithms. In this paper, techniques are developed for generating all scheduling and retiming solutions for a strongly connected data-flow graph, allowing a designer to explore the space of possible implementations. Formulations are developed for two scheduling problems. The first scheduling problem assumes a bit-parallel target architecture. The formulation for this problem is general because it considers retiming the dataflow graph as part of scheduling, and this formulation reduces to the retiming formulation as a special case. The second scheduling problem assumes a bit-serial target architecture. Based on these formulations, the conditions for a legal scheduling solution are derived, and a systematic technique is presented for exhaustively generating all legal scheduling solutions for a strongly connected data-flow graph. Since retiming is a special case of scheduling, this systematic technique can also be used for exhaustively generating all legal retiming solutions. A technique is also developed for exhaustively generating only those bit-parallel schedules which satisfy a given set of resource constraints, The techniques for exhaustively generating scheduling and retiming solutions are demonstrated for several filters. For example, we show that a simple filter such as the biquad has 224 possible retiming solutions for a latency of one time unit. We also show that a fifth-order wave digital elliptic filter has 4.7 million and 580 million scheduling solutions for iteration periods of 17 and 18, respectively.
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 characteriza...
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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.
Computationally efficient algorithms which perform speech activity detection have significant potential economic and labor saving benefit, by automating an extremely tedious manual process. In many applications, it is...
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ISBN:
(纸本)0819429163
Computationally efficient algorithms which perform speech activity detection have significant potential economic and labor saving benefit, by automating an extremely tedious manual process. In many applications, it is desirable to extract intervals of speech which are bounded by segments of other signal types (fax/modem, music, static, dial tones, etc.). In the past, algorithms which successfully discriminate between speech and one specific other signal type have been developed. Frequently, these algorithms fail when the specific non-speech signal is replaced by a different non-speech signal. Little work has been done on combining such discriminators in order to solve the general speech vs. non-speech discrimination problem. Typically, several signal specific discriminators are blindly combined with predictable negative results. Moreover, when a large number of discriminators are involved, dimension reduction is achieved using Principal Components, which optimally compresses signalvariance into the fewest number of dimensions. Unfortunately, these new coordinates are not necessarily optimal for discrimination. In this paper we apply graphical tools to determine a set of discriminators which produce excellent speech vs. non-speech clustering, thereby eliminating the guesswork in selecting good feature vectors. This cluster structure provides a basis for a general multivariate speech vs. non-speech discriminator, which compares very favorably with the TALKATIvE speech extraction algorithm.
We consider two general procedures for constructing the nearest approximation of a given matrix by one with any lower rank and any linear structure. Nearness can be measured in any matrix norm. Structured low rank mat...
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ISBN:
(纸本)0819429163
We consider two general procedures for constructing the nearest approximation of a given matrix by one with any lower rank and any linear structure. Nearness can be measured in any matrix norm. Structured low rank matrices arise in various applications, including image enhancement and model reduction. In practice, the empirical data collected in the matrix often either do not maintain the specified structure or do not induce the desirable rank. It is an important task to search for the nearest structured lower rank approximation of a given matrix. The techniques developed in this paper can easily be implemented for numerical computation. In particular, it is shown that the computations can be approached using efficient optimization packages. The special case of Toeplitz structure using the Frobenius matrix norm is discussed in detail to illustrate the ideas, and numerical tests are reported. The procedures developed herein can be generalized to consider a much broader range of approximation problems.
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