In this paper we introduce a. multi-scale deconvolution technique performed in the scale-domain. In sensor array applications such as in radar, sonar and seismic processing, the sensor outputs are modeled as the convo...
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ISBN:
(纸本)0819432938
In this paper we introduce a. multi-scale deconvolution technique performed in the scale-domain. In sensor array applications such as in radar, sonar and seismic processing, the sensor outputs are modeled as the convolution of the unknown source signal with various unknown system impulse responses that are scaled versions of each other with unknown scale parameters. In many applications these signals or the scaling parameters are needed to be estimated only from the sensor outputs. In our earlier work, we estimated the unknown scale parameters by using properties of the scale transform and then employed existing deconvolution algorithms. Here, we derive the multiscale blind deconvolution algorithm in the scale transform domain. The performance of the method is illustrated using simulation examples.
It is shown how some simple multilinear transformations may be used to generate an alternative, and potentially faster, version of the BLISS algorithm for blind signal separation. The BLISS algorithm performs an indep...
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ISBN:
(纸本)0819432938
It is shown how some simple multilinear transformations may be used to generate an alternative, and potentially faster, version of the BLISS algorithm for blind signal separation. The BLISS algorithm performs an independent component analysis of the type proposed by Comon but uses a different method for estimating the pairwise rotation angles. It has been applied to a wide range of communication signals and proved extremely successful in practice. The reformulated version of BLISS requires less arithmetic operations provided the number of signals to be separated is fairly small (similar to 3 to 5) as found in a range of important communication scenarios.
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.
It is well known that high-dimensional integrals can be solved with Monte Carlo algorithms. Recently, it was discovered that there is a relationship between low discrepancy sets and the efficient evaluation of higher-...
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ISBN:
(纸本)0819432938
It is well known that high-dimensional integrals can be solved with Monte Carlo algorithms. Recently, it was discovered that there is a relationship between low discrepancy sets and the efficient evaluation of higher-dimensional integrals. Theory suggests that for midsize dimensional problems, algorithms based on low discrepancy sets should out perform all other existing methods by an order of magnitude in terms of the number of sample points used to evaluate the integrals. We show that the field of image processing can potentially take advantage of specific properties of low discrepancy sets. To illustrate this, we applied the theory of low discrepancy sequences to some relatively simple image processing and computer vision related operations such as the estimation of gray level image statistics, fast location of objects in a binary image and the reconstruction of images from a sparse set of points. Our experiments show that compared to standard methods, the proposed new algorithms are faster and statistically more robust. Classical low discrepancy sets based on the Halton and Sobol' sequences were investigated thoroughly and showed promising results. The use of low discrepancy sequences in image processing for image characterization, understanding and object recognition is a novel and promising area for further investigation.
This paper presents novel methods of designing analog Cellular Nonlinear (Neural) Networks (CNNs) to implement very low-noise binary addition. In these techniques the continuous characteristic of the current that char...
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ISBN:
(纸本)0819432938
This paper presents novel methods of designing analog Cellular Nonlinear (Neural) Networks (CNNs) to implement very low-noise binary addition. In these techniques the continuous characteristic of the current that charges (discharges) the load capacitor leads to a virtually switching free addition process that significantly reduces the switching noise. This switching mechanism also leads to higher slew of output voltage during the transitions which in turn reduces the cross talk. Simulation results demonstrate a three orders of magnitude reduction in the noise generated by this structure compared to that generated by a digital adder running at the same speed. This very good noise performance of these new adder structures makes them suitable choices for low to moderate speed high precision mixed signal applications.
Investigating a number of different integral transforms uncovers distinct patterns in the type of scale-based convolution theorems afforded by each. It is shown that scaling convolutions behave in quite a similar fash...
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Investigating a number of different integral transforms uncovers distinct patterns in the type of scale-based convolution theorems afforded by each. It is shown that scaling convolutions behave in quite a similar fashion to translational convolution in the transform domain, such that the many diverse transforms have only a few different forms for convolution theorems. The hypothesis is put forth that the space of integral transforms is partitionable based on these forms.
It is not uncommon for remote sensing systems to produce in excess of 100 Mbytes/sec. Los Alamos National Laboratory designed a reconfigurable computer to tackle the signal and image processing challenges of high band...
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It is not uncommon for remote sensing systems to produce in excess of 100 Mbytes/sec. Los Alamos National Laboratory designed a reconfigurable computer to tackle the signal and image processing challenges of high bandwidth sensors. Reconfigurable computing, based on field programmable gate arrays, offers ten to one hundred times the performance of traditional microprocessors for certain algorithms. This paper discusses the architecture of the computer and the source of performance gains, as well as an example application. The calculation of multiple matched filters applied to multispectral imagery, showing a performance advantage of forty-five over Pentium ii (450 MHz), is presented as an exemplar of algorithms appropriate for this technology.
The idea is (i) to use a variable energy allocation per signaling symbol and (ii) to pseudorandomize the order in which signaling symbols are transmitted. This strategy will allow the most important part of the sensor...
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The idea is (i) to use a variable energy allocation per signaling symbol and (ii) to pseudorandomize the order in which signaling symbols are transmitted. This strategy will allow the most important part of the sensor data to be (i) decorrelated against periodic unequal power interfering noise and specifically (ii) where that noise is purposely tailored or allocated in an attempt to provide maximum disruption of information transport as in 'smart' jamming. In a very real sense, perfect compression followed by this method leads to a genre of spread spectrum known as Time Hopping (TH).
Cauchy-Vandermonde matrices are related with rational interpolation problems. In this paper we consider the general case in which multiple poles can appear. Fast algorithms for solving the corresponding linear systems...
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Cauchy-Vandermonde matrices are related with rational interpolation problems. In this paper we consider the general case in which multiple poles can appear. Fast algorithms for solving the corresponding linear systems are presented. Some results on the total positivity of these matrices and other related matrices are included.
Fault tolerance is increasingly important as society has come to depend on computers for more and more aspects of daily life. The current concern about the Y2K problems indicates just how we much we depend on accurate...
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Fault tolerance is increasingly important as society has come to depend on computers for more and more aspects of daily life. The current concern about the Y2K problems indicates just how we much we depend on accurate computers. This paper describes work on time-shared TMR, a technique which is used to provide arithmetic operations that produce correct results in spite of circuit faults.
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