This paper introduces a new form of observation distributions for hidden Markov models (HMMs), combining subvector quantization and mixtures of discrete distributions. Despite what is generally believed, we show that ...
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This paper introduces a new form of observation distributions for hidden Markov models (HMMs), combining subvector quantization and mixtures of discrete distributions. Despite what is generally believed, we show that discrete-distribution HMMs can outperform continuous-density HMMs at significantly faster decoding speeds. Performance of the discrete HMMs is improved by using product-code vector quantization (VQ) and mixtures of discrete distributions. The decoding speed of the discrete HMMs is also improved by quantizing subvectors of coefficients, since this reduces the number of table lookups needed to compute the output probabilities. We present efficient training and decoding algorithms for the discrete-mixture HMMs (DMHMMs). Our experimental results in the air-travel information domain show that the high level of recognition accuracy of continuous-mixture-density HMMs (CDHMMs) can be maintained at significantly faster decoding speeds. Moreover, we show that when the same number of mixture components is used in DMHMMs and CDHMMs, the new models exhibit superior recognition performance. (C) 2000 Academic Press.
We define alternant codes over a commutative ring R and a corresponding key equation. We show that when the ring is a domain, e.g. the p-adic integers, the error-locator polynomial is the unique monic minimal polynomi...
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We define alternant codes over a commutative ring R and a corresponding key equation. We show that when the ring is a domain, e.g. the p-adic integers, the error-locator polynomial is the unique monic minimal polynomial (equivalently, the unique shortest linear recurrence) of the finite sequence of syndromes and that it can be obtained by algorithm MR of Norton. When R is a local ring, we show that the syndrome sequence may have more than one (monic) minimal polynomial, but that all the minimal polynomials coincide modulo the maximal ideal of R. We characterise the set of minimal polynomials when R is a Hensel ring. We also apply these results to decoding alternant codes over a local ring R: it is enough to find any monic minimal polynomial over R and to find its roots in the residue field. This gives a decoding algorithm for alternant codes over a finite chain ring, which generalizes and improves a method of Interlando et. al. for BCH and Reed-Solomon codes over a Galois ring.
We analyze Gallager codes by employing a simple mean-field approximation that distorts the model geometry and preserves important interactions between sites. The method naturally recovers the probability propagation d...
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ISBN:
(纸本)0262122413
We analyze Gallager codes by employing a simple mean-field approximation that distorts the model geometry and preserves important interactions between sites. The method naturally recovers the probability propagation decoding algorithm as an extremization of a proper free-energy. We find a thermodynamic phase transition that coincides with information theoretical upper-bounds and explain the practical code performance in terms of the free-energy landscape.
This paper first presents a new array data structure to represent the Huffman tree. The memory required in the proposed data structure is less than the previous methods (Huffman, 1952;Roman, 1992), which also use arra...
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This paper first presents a new array data structure to represent the Huffman tree. The memory required in the proposed data structure is less than the previous methods (Huffman, 1952;Roman, 1992), which also use array data structure to store the corresponding Huffman tree, and is the lower bound of the one in (Hashemian, 1995). We then present an efficient Huffman decoding algorithm based on the proposed data structure;given a Huffman code, the search time for finding the source symbol is O(d), where d denotes the depth of the Huffman tree. This time bound is equal to the ones in (Hashemian, 1995;Huffman, 1952;Roman, 1992). Some experimentations on real images are carried out to demonstrate the performance of space and search time among our method and the previous ones. (C) 1997 Elsevier Science B.V.
Based on the breadth-first search manner and the level-compression technique, this letter first presents a new ai ray data structure to represent the classical Huffman tree. Then, the decoding algorithm is given. Both...
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Based on the breadth-first search manner and the level-compression technique, this letter first presents a new ai ray data structure to represent the classical Huffman tree. Then, the decoding algorithm is given. Both the memory and the decoding time required in the proposed method are less than those of previous methods. Some experimentations are carried out to demonstrate the advantages of the proposed method. In fact, the proposed algorithm can be applied to the canonical Huffman tree.
It is shown that decoding of cyclic codes in the DFT domain is equivalent to an appropriate deconvolution problem. A two-dimensional (2-D) generalization of Blahut's one-dimensional (1-D) linear complexity theorem...
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It is shown that decoding of cyclic codes in the DFT domain is equivalent to an appropriate deconvolution problem. A two-dimensional (2-D) generalization of Blahut's one-dimensional (1-D) linear complexity theorem is obtained and utilized to determine the error-correcting capability of 2-D BCH codes, as afforded by code's defining array of zeros, with regard to correction of burst-errors. The 2-D linear complexity theorem is further utilized to present a new approach for decoding of cyclic codes, in general, and 2-D BCH codes in particular, An alternative exposition of Blahut's decoding algorithms, in the DFT domain, for random and burst error correction in 2-D BCH codes is given from deconvolution viewpoint. Some modifications for efficient implementation of Blahut's decoding algorithms for random and burst error correction are suggested and improved decoding algorithms are presented. It is shown that the improved decoding algorithm requires at most half the number of passes through the Berlekamp-Massey algorithm compared to the Blahut's decoding algorithm, It is shown that Blahut's decoding algorithms have optimal error-correcting capability and improved decoding algorithms have less computational complexity, A comparative study of various time-and spectral-domain implementations of 2-D BCH decoding algorithms is also given.
Iterated function systems (IFS's) have received great attention in encoding and decoding fractal images, Barnsley has shown that IFS's for image compression can achieve a very high compression ratio for a sing...
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Iterated function systems (IFS's) have received great attention in encoding and decoding fractal images, Barnsley has shown that IFS's for image compression can achieve a very high compression ratio for a single image, However, the major drawback of such a technique is the large computation load required to both encode and decode a fractal image, In this paper, we provide a novel algorithm to decode IFS codes, The main features of this algorithm are that it is very suitable for parallel implementation and has no transient behavior, Also, from the decoding process of this method we can understand the encoding procedure explicitly, One example is illustrated to demonstrate the quality of its performance.
Low-density generator matrix with iterative belief propagation decoding and comma-free source codes are natural choices for noisy channel encoding and source coding, respectively. In earlier work, We found that avoidi...
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ISBN:
(纸本)0780344081
Low-density generator matrix with iterative belief propagation decoding and comma-free source codes are natural choices for noisy channel encoding and source coding, respectively. In earlier work, We found that avoiding 6 cycles had little impact on the performance of a code established by performing a fixed number of decoding algorithm iterations. In this work, we carried on a more detailed investigation of the decoding algorithm and found that the comma-free codes call be effectively used as an outer error-detection-correction-code for a low-density generator matrix inner code.
An algorithm for finding minimum-weight words in large linear codes is developed. It improves all previous attacks on the public-key cryptosystems based on codes and it notably points out some weaknesses in McEliece...
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An algorithm for finding minimum-weight words in large linear codes is developed. It improves all previous attacks on the public-key cryptosystems based on codes and it notably points out some weaknesses in McEliece's cipher. We also determine with it the minimum distance of some BCH codes of length 511.
A novel construction for encoded tamed frequency modulation (TFM) is introduced which is based on the principles of generalized concatenation. The inner TFM is partitioned into nested subsystems which increases the fr...
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A novel construction for encoded tamed frequency modulation (TFM) is introduced which is based on the principles of generalized concatenation. The inner TFM is partitioned into nested subsystems which increases the free Euclidean distances. In order to obtain a large distance among the nested TFM subsystems, the scrambler matrices ha ce to be computed which transfer the original TFM into equivalent TFM with better partitioning properties. Then outer convolutional codes with different error-correcting capabilities are used to protect the partitioning. The new concatenated and generalized concatenated constructions were simulated in an additive white Gaussian noise channel, A multistep decoding algorithm based on soft-output demodulation was used. We present various simulation results which show a significant coding gain in comparison with the best known trellis codes having the same trellis state complexity.
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