A high-throughput lossless data compression IP core built around a CAM-based dictionary whose number of available entries and data word width adjust to the characteristics of the incoming data stream is presented. The...
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A high-throughput lossless data compression IP core built around a CAM-based dictionary whose number of available entries and data word width adjust to the characteristics of the incoming data stream is presented. These two features enhance model adaptation to the input data, improving compression efficiency, and enable greater throughputs as a multiplicity of bytes can be processed per cycle. A parsing mechanism adjusts the width of dictionary words to natural words while the length of the dictionary grows from an initial empty state to a maximum value defined as a run-time configuration parameter. The compressor/decompressor architecture was prototyped on an FPGA-based PCI board. An ASIC hard-macro was subsequently implemented and achieved a throughput of more than 1 gigabyte per second when clocking at 277 MHz on a high-performance, 0.13 mu m, eight-layer copper CMOS process.
All-optical generation of 40 GHz pulse trains with arbitrary binary code patterns from a 10 GHz uniform input pulse train using lattice-form Mach-Zehnder interferometers is experimentally demonstrated. The device is f...
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All-optical generation of 40 GHz pulse trains with arbitrary binary code patterns from a 10 GHz uniform input pulse train using lattice-form Mach-Zehnder interferometers is experimentally demonstrated. The device is fabricated on a silica-based planar lightwave circuit, which is based on a buried channel waveguide structure with an index difference of 1.2%.
A new technique, called inter-band compensated prediction, for coding colour and multispectral images is presented. It is suitable to use for coding any spectral domain and can code colour and multispectral images wit...
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A new technique, called inter-band compensated prediction, for coding colour and multispectral images is presented. It is suitable to use for coding any spectral domain and can code colour and multispectral images with any number of bands. This technique is based on the same principles as the very efficient motion compensated prediction largely used in video coding. Thus, each band is predicted in the spectral direction by compensating the differences in the neighbouring bands and then coding the prediction error spatially by another method. This is a forward adaptive prediction and the information used for compensation is coded as side information with prediction error. The comparison of the coding results with the state-of-the-art coding algorithms, based on spectral transformations, proves that this technique is very efficient and can even outperform them. In addition, compensation can be combined with any spatial coder that allows lossless, lossy and scalable coding of any spectral content of the image. It has also the advantages of being simple to implement and to use with parallel architectures.
Toric codes are evaluation codes obtained from an integral convex polytope P. Rn and finite field F-q. They are, in a sense, a natural extension of Reed - Solomon codes, and have been studied recently in [ V. Diaz, C....
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Toric codes are evaluation codes obtained from an integral convex polytope P. Rn and finite field F-q. They are, in a sense, a natural extension of Reed - Solomon codes, and have been studied recently in [ V. Diaz, C. Guevara, and M. Vath, Proceedings of Simu Summer Institute, 2001], [ J. Hansen, Appl. Algebra Engrg. Comm. Comput., 13 ( 2002), pp. 289 - 300;coding theory, Cryptography and Related Areas ( Guanajuato, 1998), Springer, Berlin, pp. 132 - 142], and [ D. Joyner, Appl. Algebra Engrg. Comm. Comput., 15 ( 2004), pp. 63 - 79]. In this paper, we obtain upper and lower bounds on the minimum distance of a toric code constructed from a polygon P subset of R-2 by examining Minkowski sum decompositions of subpolygons of P. Our results give a simple and unifying explanation of bounds in Hansen's work and empirical results of Joyner;they also apply to previously unknown cases.
A new stopping rule for turbo codes, the input-output consistency (IOC) check is presented. It is based on an extended maximum a posteriori algorithm that also outputs (hard) extrinsic estimates oil the coded bits. In...
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A new stopping rule for turbo codes, the input-output consistency (IOC) check is presented. It is based on an extended maximum a posteriori algorithm that also outputs (hard) extrinsic estimates oil the coded bits. In parallel, the hard decisions of the info bits are re-encoded and if the two sequences coincide, iterative decoding is stopped. Remarkably. IOC beats other known stopping rules ill terms of error rate and convergence speed, closely approaching ideal 'Genie'-aided decoding.
A novel decoding algorithm for the JPEG Huffman code is presented, in which the alternating current (AC) Huffman table is partitioned into four modules. According to this partition, a direct mapping technique is devel...
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A novel decoding algorithm for the JPEG Huffman code is presented, in which the alternating current (AC) Huffman table is partitioned into four modules. According to this partition, a direct mapping technique is developed to decode Huffman codewords without any searching or matching operations. Therefore, an algorithm based on this technique can save several controlling circuits and will be simple for the hardware implementation. There are also two other merits: first, the run/size symbols and codeword lengths can be obtained directly;and, next, it is not necessary to store any AC Huffman codewords in the memory space at the decoding end. As a result, the overall behaviour of the developed algorithm is better than the conventional methods. This is illustrated through a mathematical verification using the Big-O notation and a hardware simulation using hardware description language. Tables of comparison results are included in the paper. Furthermore, a VLSI architecture of this proposed algorithm is also developed and included.
A latin square is a matrix of size n x n with entries from the set {1.....n}, such that each row and each column is a permutation on {1.....n}. We show how to construct a latin square such that for any two distinct ro...
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A latin square is a matrix of size n x n with entries from the set {1.....n}, such that each row and each column is a permutation on {1.....n}. We show how to construct a latin square such that for any two distinct rows, the prefixes of length h of the two rows share at most about h(2)/n elements. This upper bound is close to optimal when contrasted with a lower bound derived from the Second Johnson bound [6]. (c) 2005 Elsevier B.V. All rights reserved.
Data-centric networks are gaining importance because of their application in several areas such as sensor networks. One of the key challenges in such networks is the resource constraint under which the nodes must oper...
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Data-centric networks are gaining importance because of their application in several areas such as sensor networks. One of the key challenges in such networks is the resource constraint under which the nodes must operate. Under these circumstances, the trend is to shift a significant percentage of the computational burden from the individual nodes to a central decoder. The problem of error-resilient communications in data-centric networks is addressed by taking a joint source-channel decoding (JSCD) approach. This improvement in error resilience is achieved by using the source statistics at the decoder, thereby ensuring that the encoder complexity is not increased. Specifically, an optimal JSCD is designed for multiple-access source code (MASC)-encoded Markov sources. This is the first known attempt at designing a JSCD for the general case of correlated sources with memory. Simulation results demonstrate that the proposed decoder outperforms the traditional MASC decoder by up to 10 dB in some cases. The results indicate that significant error resilience is possible even without using forward error-correcting codes at the encoder, which is important in encoder-resource constrained applications.
We consider liar games in which player Paul must ask one full batch of questions, receive all answers, and then ask a second and final batch of questions. We show that the effect of this restriction is asymptotically ...
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We consider liar games in which player Paul must ask one full batch of questions, receive all answers, and then ask a second and final batch of questions. We show that the effect of this restriction is asymptotically negligible. The strategy for Paul is given explicitly.
This paper presents an efficient variable block size motion estimation algorithm for use in real-time H.264 video encoder implementation. In this recursive motion estimation algorithm, results of variable block size m...
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This paper presents an efficient variable block size motion estimation algorithm for use in real-time H.264 video encoder implementation. In this recursive motion estimation algorithm, results of variable block size modes and motion vectors previously obtained for neighboring macroblocks are used in determining the best mode and motion vectors for encoding the current macroblock. Considering only a limited number of well chosen candidates helps reduce the computational complexity drastically. An additional fine search stage to refine the initially selected motion vector enhances the motion estimator accuracy and SNR performance to a value close to that of full search algorithm. The proposed methods result in over 80% reduction in the encoding time over full search reference implementation and around 55% improvement in the encoding time over the fast motion estimation algorithm (FME) of the reference implementation. The average SNR and compression performance do not show significant difference from the reference implementation. Results based on a number of video sequences are presented to demonstrate the advantage of using the proposed motion estimation technique. (c) 2005 Elsevier B.V. All rights reserved.
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