Novel arithmetic units are needed to achieve the cost, performance, power, and functionality requirements of emerging multimedia systems. This paper presents the design and implementation of a 64-bit arithmetic and lo...
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ISBN:
(纸本)0819450782
Novel arithmetic units are needed to achieve the cost, performance, power, and functionality requirements of emerging multimedia systems. This paper presents the design and implementation of a 64-bit arithmetic and logic unit (ALU) for multimedia processing. The 64-bit ALU supports subword-parallel processing by allowing one 64-bit, two 32-bit, four 16-bit, or eight 8-bit operations to be performed in parallel. In addition to conventional ALU operations, the ALU also supports several operations for enhanced multimedia processing including parallel compare, parallel average, parallel minimum, parallel maximum, and parallel shift and add. To efficiently implement a variety of multimedia applications, the ALU supports saturating and wrap-around arithmetic operations on unsigned and two's complement operands. This paper compares the area and delay of the 64-bit multimedia ALU to those of a more conventional 64-bit ALU.
In this paper, we present a new class of representations of signals in the time-frequency (TF) plane. These representations are complex valued, linear, and satisfy reconstruction conditions in which the signal and its...
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ISBN:
(纸本)0819429163
In this paper, we present a new class of representations of signals in the time-frequency (TF) plane. These representations are complex valued, linear, and satisfy reconstruction conditions in which the signal and its complex spectrum may be uniquely reconstructed from their TF representation. These surfaces are generalizations of one-dimensional linear transforms with which they share many properties.. The primary advantage of these representations is that the phase of the surface may be used to recover signal information which is not contained in real TF surfaces. Linearity guarantees that cross-terms normally associated with TF distributions do not exist in these representations. Several examples of invertible surfaces are presented, and it is demonstrated that these surfaces agree with normal intuition. Finally, a method, based on the phase gradient, is proposed as a method of modifying Fourier surfaces to produce representations which are more focused or more concentrated in time and frequency.
We are presenting a new method for super resolution tracking of frequency modulated sinusoids in white noise. The method is specifically designed to handle the rapid transient problem, i.e. the problem of tracking a c...
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ISBN:
(纸本)9780819468451
We are presenting a new method for super resolution tracking of frequency modulated sinusoids in white noise. The method is specifically designed to handle the rapid transient problem, i.e. the problem of tracking a continuous, rapidly changing instantaneous frequency contour. The proposed method employs to components: 1) an adaptive generalized scale transform 1, 2 which applies a localized change of time-frequency coordinates within the given signal, and 2) an estimation of signal parameters by rotational invariance techniques 3 (ESPRIT). With experiments we have shown that the proposed method provides a significantly higher estimation accuracy than conventional methods. 3 With an optimal choice of transform parameters the estimation error can be reduced dramatically. Error reductions of over 40% have been observed.
In this paper, we consider the use of a seismic sensor array for the localization and tracking of a wideband moving source. The proposed solution consists of two steps: source Direction-Of-Arrival (DOA) estimation and...
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ISBN:
(纸本)9780819468451
In this paper, we consider the use of a seismic sensor array for the localization and tracking of a wideband moving source. The proposed solution consists of two steps: source Direction-Of-Arrival (DOA) estimation and localization via DOA estimates. Three DOA estimation methods are considered. The Covariance Matrix Analysis and the Surface Wave Analysis are previously published DOA estimation algorithms shown to be effective in the localization of a stationary wideband source. This paper investigates their performance on moving wideband sources. A novel DOA estimation algorithm, the Modified Kirlin's Method was also developed for the localization of a moving Source. The DOAs estimated by these algorithms are combined rising a least-squares optimization for source localization. The application of these algorithms to real-life data show the effectiveness of both the Surface Wave Analysis and the Modified Kirlin's Method in locating and tracking a wideband moving source.
Given the moments of a time-frequency distribution, one can, in principle, construct the characteristic function from which one then obtains the distribution by Fourier transformation. However, often one can not find ...
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ISBN:
(纸本)9780819468451
Given the moments of a time-frequency distribution, one can, in principle, construct the characteristic function from which one then obtains the distribution by Fourier transformation. However, often one can not find a closed form for the characteristic function and hence one can not obtain the distribution in a direct manner. We formulate the problem of constructing time-frequency representations from moments without first constructing the characteristic function. Our method is based on expanding the distribution in terms of a complete set of functions where the expansion coefficients are dependent directly on the moments. We apply the method to a case where the even moments are manifestly positive which is a necessary condition for obtaining a proper time-frequency representation.
We present a solution to a complex multi-tone transient detection problem to illustrate the integrated use of symbolic and numeric processing techniques which are supported by well-established underlying models. Examp...
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ISBN:
(纸本)0819422347
We present a solution to a complex multi-tone transient detection problem to illustrate the integrated use of symbolic and numeric processing techniques which are supported by well-established underlying models. Examples of such models include synchronous dataflow for numeric processing and the blackboard paradigm for symbolic heuristic search. Our transient detection solution serves to emphasize the importance of developing system design methods and tools which can support the integrated use of well- established symbolic and numerical models of computation. Recently, we incorporated a blackboard-based model of computation underlying the Integrated processing and Understanding of signals (IPUS) paradigm into a system-level design environment for numeric processing called Ptolemy. Using the IPUS/Ptolemy environment, we are implementing our solution to the multi-tone transient detection problem.
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. ...
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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.
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.
In this paper, a new Fourier domain reconstruction algorithm is presented which utilizes the information contained in the known region of the spectrum to estimate the frequency samples in the missing-cone area. Unlike...
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ISBN:
(纸本)0819412767
In this paper, a new Fourier domain reconstruction algorithm is presented which utilizes the information contained in the known region of the spectrum to estimate the frequency samples in the missing-cone area. Unlike conventional two-dimensional extrapolation techniques, this method uses bi-directional extrapolation to maximize the amount of known information in each extrapolation step. By fully utilizing the information of the measured data, the resulting image provides a more accurate estimation of the electron density distribution. The resolution improvement achieved is mainly due to the proper utilization of the available information in the measurements during the image formation process.
We consider the problem of recovering signals from noisy indirect observations under the additional a priori information that the signal is believed to be slowly varying except at all unknown number of points where it...
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ISBN:
(纸本)9780819468451
We consider the problem of recovering signals from noisy indirect observations under the additional a priori information that the signal is believed to be slowly varying except at all unknown number of points where it may have discontinuities of unknown size. The model problem is a linear deconvolution problem. To take advantage of the qualitative prior information available, we use a non-stationary Markov model with the variance of the innovation process also unknown, and apply Bayesian techniques to estimate both the signal and the prior variance. We propose a fast iterative method for computing a MAP estimates and we show that, with a rather standard choices of the hyperpriors, the algorithm produces the fixed point iterative solutions of the total variation and of the Perona-Malik regularization methods. We also demonstrate that, unlike the non-statistical estimation methods, the Bayesian approach leads to a very natural reliability assessment of edge detection by a Markov Chain Monte Carlo (MCMC) based analysis of the posterior.
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