The ULv decomposition (ULvD) is an important member of a class of rank-revealing two-sided orthogonal decompositions used to approximate the singular value decomposition (SvD). The ULvD can be updated and downdated mu...
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The ULv decomposition (ULvD) is an important member of a class of rank-revealing two-sided orthogonal decompositions used to approximate the singular value decomposition (SvD). The ULvD can be updated and downdated much faster than the SvD, hence its utility in the solution of recursive total least squares (TLS) problems. However, the robust implementation of ULvD after the addition and deletion of rows (called updating and downdating respectively) is not altogether straightforward. When updating or downdating the ULvD, the accurate computation of the subspaces necessary to solve the TLS problem is of great importance. In this paper, algorithms are given to compute simple parameters that can often show when good subspaces have been computed.
A digital audio watermarking scheme of low complexity is proposed in this research as an effective way to deter users from misusing or illegally distributing audio data. Previous work on audio watermarking has primari...
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A digital audio watermarking scheme of low complexity is proposed in this research as an effective way to deter users from misusing or illegally distributing audio data. Previous work on audio watermarking has primarily focused on the inaudibility of the embedded watermark and its robustness against attacks such as compression and noise. In this research, special attention is paid to the synchronization attack caused by casual audio editing or malicious random cropping, which is a low-cost yet effective attack to watermarking algorithms developed before. The proposed scheme is based on audio content analysis and watermark embedding in the Fourier transform domain. A blind watermark detection technique is developed to identify the embedded watermark under various types of attacks.
Two methods of focusing synthetic aperture radar (SAR) images are compared. Both a conventional subaperture cross-correlation method and a new phase gradient autofocus (PGA) algorithm developed at Sandia National Labo...
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ISBN:
(纸本)0819406945
Two methods of focusing synthetic aperture radar (SAR) images are compared. Both a conventional subaperture cross-correlation method and a new phase gradient autofocus (PGA) algorithm developed at Sandia National Laboratories are shown to perform well if high-order phase errors are not present. With the introduction of significant high-order phase errors [e.g., due to uncompensated platform motion], both algorithms suffer a loss in performance. However, relative performance degradation is less for PGA than for the subaperture focusing technique. An explanation is presented for the observed behavior of the two autofocus techniques.
Compressive Sensing (CS) is a novel scheme, in which a signal that is sparse in a known transform domain can be reconstructed using fewer samples. The signal reconstruction techniques are computationally intensive and...
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ISBN:
(纸本)9781628410464
Compressive Sensing (CS) is a novel scheme, in which a signal that is sparse in a known transform domain can be reconstructed using fewer samples. The signal reconstruction techniques are computationally intensive and have sluggish performance, which make them impractical for real-time processing applications. The paper presents novel architectures for Orthogonal Matching Pursuit algorithm, one of the popular CS reconstruction algorithms. We show the implementation results of proposed architectures on FPGA, ASIC and on a custom many-core platform. For FPGA and ASIC implementation, a novel thresholding method is used to reduce the processing time for the optimization problem by at least 25%. Whereas, for the custom many-core platform, efficient parallelization techniques are applied, to reconstruct signals with variant signal lengths of N and sparsity of m. The algorithm is divided into three kernels. Each kernel is parallelized to reduce execution time, whereas efficient reuse of the matrix operators allows us to reduce area. Matrix operations are efficiently paralellized by taking advantage of blocked algorithms. For demonstration purpose, all architectures reconstruct a 256-length signal with maximum sparsity of 8 using 64 measurements. Implementation on Xilinx virtex-5 FPGA, requires 27.14 mu s to reconstruct the signal using basic OMP. Whereas, with thresholding method it requires 18 mu s. ASIC implementation reconstructs the signal in 13 mu s. However, our custom many-core, operating at 1.18 GHz, takes 18.28 mu s to complete. Our results show that compared to the previous published work of the same algorithm and matrix size, proposed architectures for FPGA and ASIC implementations perform 1.3x and 1.8x respectively faster. Also, the proposed many-core implementation performs 3000x faster than the CPU and 2000x faster than the GPU.
This paper studies an approach to solve the problem of color purification for images of scanned paper maps in an experimental manner. The mathematical foundation of the approach is briefly outlined. A computationally ...
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This paper studies an approach to solve the problem of color purification for images of scanned paper maps in an experimental manner. The mathematical foundation of the approach is briefly outlined. A computationally feasible algorithm is then proposed. This algorithm is tested through real life testing. Results indicate that this approach not only restores and purifies colors of the map digitally. It compresses the data of the image files too.
Exact computations, performed with residues, occur in Number Theoretic Transforms and Residue Number System implementations. Once thought awkward to implement with standard logic circuits, the application of efficient...
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We introduce the use of multidimensional logarithmic number system (MDLNS) as a generalization of the classical 1-D logarithmic number system (LNS) and analyze its use in DSP applications. The major drawback of the LN...
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We introduce the use of multidimensional logarithmic number system (MDLNS) as a generalization of the classical 1-D logarithmic number system (LNS) and analyze its use in DSP applications. The major drawback of the LNS is the requirement to use very large ROM arrays in implementing the additions and subtraction and it limits its use to low-precision applications. MDLNS allows exponential reduction of the size of the ROMs used without affecting the speed of the computational process: moreover, the calculations over different bases and digits are completely independent, which makes this particular representation perfectly suitable for massively parallel DSP architectures. The use of more than one base has at least two extra advantages. Firstly, the proposed architecture allows us to obtain the final result straightforwardly in binary form, thus, there is no need of the exponential amplifier, used in the known LNS architectures. Secondly, the second base can be optimized in accordance to the specific digital filter characteristics. This leads to dramatic reduction of the exponents used and, consequently, to large area savings. We offer many examples showing the computational advantages of the proposed approach.
This paper describes a scheduling method for hard real-time Digital signalprocessing (DSP) applications, implemented on a multi-processor. Due to the very high operating frequencies of DSP applications (typically hun...
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ISBN:
(纸本)0819416207
This paper describes a scheduling method for hard real-time Digital signalprocessing (DSP) applications, implemented on a multi-processor. Due to the very high operating frequencies of DSP applications (typically hundreds of kHz) runtime overhead should be kept as small as possible. Because static scheduling introduces very little run-time overhead it is used as much as possible. Dynamic pre-emption of tasks is allowed if and only if it leads to better performance in spite of the extra run-time overhead. We essentially combine static scheduling with dynamic pre-emption using static priorities. Since we are dealing with hard real-time applications we must be able to guarantee at compile-time that all timing requirements will be satisfied at run-time. We will show that our method performs at least as good as any static scheduling method. It also reduces the total amount of dynamic pre-emptions compared with run time methods like deadline monotonic scheduling.
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).
Originally coined by the sensory psychologist Roger Shepard in the 1960's, chroma transforms frequency into octave equivalence classes. By extending the concept of chroma to chroma strength and how it varies over ...
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Originally coined by the sensory psychologist Roger Shepard in the 1960's, chroma transforms frequency into octave equivalence classes. By extending the concept of chroma to chroma strength and how it varies over time, we have demonstrated the utility of chroma in simplifying the processing and representation of signals dominated by harmonically-related narrowband components. These investigations have utilized an ad hoc procedure for calculating the chromagram from a given time-frequency distribution. The present paper is intended to put this ad hoc procedure on more sound mathematical ground.
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