The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Guoan Bi - One of the best experts on this subject based on the ideXlab platform.
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Prime factor algorithm of discrete cosine transform
2000 10th European Signal Processing Conference, 2000Co-Authors: Guoan Bi, Yonghong ZengAbstract:Prime factor fast algorithms are Computationally efficient for various discrete transforms. However, they generally need an index mapping process to convert one-dimensional input sequence into a two-dimensional array, which results in a substantially Computational overhead and an irregular Computational Structure. This letter attempts to minimize the computation overhead by a simple and general mapping procedure.
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Fast algorithms for generalized discrete Hartley transform of composite sequence lengths
IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 2000Co-Authors: Guoan Bi, Yan Qiu Chen, Yonghong ZengAbstract:This paper presents fast algorithms for type-II, type-III, and type-IV generalized discrete Hartley transform. In particular, new odd-factor algorithms are derived to support transforms whose sequence length contains multiple odd factors. By jointly using the odd-factor and radix-2 algorithms, fast computation for arbitrarily composite sequence length can be achieved. Compared to other reported algorithms, the proposed ones have a regular Computational Structure, achieve a substantial reduction of Computational complexity, and support a wider range of choices on the sequence length.
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Fast computation of R-dimensional DHT with size Q(L/sub 1/)/spl times/Q(L/sub 2/)/spl times/.../spl times/Q(L/sub R/)
WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000, 2000Co-Authors: Yonghong Zeng, Guoan BiAbstract:Fast algorithms are presented for multi-dimensional discrete Hartley transform (MD-DHT) with size q(l/sub 1/)/spl times/q(l/sub 2/)/spl times/.../spl times/q(l/sub r/), where q is an odd prime number, and r>1 is the number of dimensions. By using the multi-dimensional polynomial transform, the MD-DHT can be converted into a series of reduced one-dimensional DHTs. Compared to other fast algorithms, the proposed one substantially reduces the overall Computational complexity and has a simple Computational Structure.
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Prime-factor algorithms for generalised discrete Hartley transform
Electronics Letters, 1999Co-Authors: Guoan Bi, Chao LuAbstract:A prime factor fast algorithm for the type-II generalised discrete Hartley transform is presented. In addition to reducing the number of arithmetic operations and achieving a regular Computational Structure, a simple index mapping method is proposed to minimise the overall implementation complexity.
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Fast algorithms for type-III DCT of composite sequence lengths
IEEE Transactions on Signal Processing, 1999Co-Authors: Guoan BiAbstract:This correspondence presents an odd-factor algorithm for the type-III discrete cosine transform (DCT) for uniform or mixed radix decomposition. By jointly using the old-factor and the existing radix-2 algorithms, a general decomposition method for arbitrarily composite sequence length is developed. A reduction of Computational complexity can be achieved compared with that needed by other reported algorithms for M=2/sup m/. The decomposition approach has a simple Computational Structure and supports a wider range of choices for different sequence lengths.
Qianchuan Zhao - One of the best experts on this subject based on the ideXlab platform.
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Parallel implementation of OBDD-based splitting surface search for power system
2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008Co-Authors: Xiao Li, Qianchuan ZhaoAbstract:Summary form only given. Parallel Computational Structure is helpful for many complicated problems, especially those which can be divided into multiple independent simpler sub-problems. The ordered binary decision diagrams (OBDD)-based splitting surface search algorithm owns this kind of dividability, derived from the associative law of Boolean expression and the dividability of matrix operation. We have implemented the algorithm with the parallel computation Structure MPI to save up computing time.
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Parallel Implementation of OBDD-Based Splitting Surface Search for Power System
IEEE Transactions on Power Systems, 2007Co-Authors: Xiao Li, Qianchuan ZhaoAbstract:Parallel Computational Structure is helpful for many complicated problems, especially those which can be divided into multiple independent simpler sub-problems. The ordered binary decision diagrams (OBDD)-based splitting surface search algorithm owns this kind of dividability, derived from the associative law of Boolean expression and the dividability of matrix operation. We have implemented the algorithm with the parallel computation Structure MPI to save up computing time. Customized verification is available on our interactive illustrative website http://obdd.cfins.au.tsinghua.edu.cn/ (login user name: mag, password: 199707).
Yonghong Zeng - One of the best experts on this subject based on the ideXlab platform.
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Prime factor algorithm of discrete cosine transform
2000 10th European Signal Processing Conference, 2000Co-Authors: Guoan Bi, Yonghong ZengAbstract:Prime factor fast algorithms are Computationally efficient for various discrete transforms. However, they generally need an index mapping process to convert one-dimensional input sequence into a two-dimensional array, which results in a substantially Computational overhead and an irregular Computational Structure. This letter attempts to minimize the computation overhead by a simple and general mapping procedure.
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Fast algorithms for generalized discrete Hartley transform of composite sequence lengths
IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 2000Co-Authors: Guoan Bi, Yan Qiu Chen, Yonghong ZengAbstract:This paper presents fast algorithms for type-II, type-III, and type-IV generalized discrete Hartley transform. In particular, new odd-factor algorithms are derived to support transforms whose sequence length contains multiple odd factors. By jointly using the odd-factor and radix-2 algorithms, fast computation for arbitrarily composite sequence length can be achieved. Compared to other reported algorithms, the proposed ones have a regular Computational Structure, achieve a substantial reduction of Computational complexity, and support a wider range of choices on the sequence length.
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Fast computation of R-dimensional DHT with size Q(L/sub 1/)/spl times/Q(L/sub 2/)/spl times/.../spl times/Q(L/sub R/)
WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000, 2000Co-Authors: Yonghong Zeng, Guoan BiAbstract:Fast algorithms are presented for multi-dimensional discrete Hartley transform (MD-DHT) with size q(l/sub 1/)/spl times/q(l/sub 2/)/spl times/.../spl times/q(l/sub r/), where q is an odd prime number, and r>1 is the number of dimensions. By using the multi-dimensional polynomial transform, the MD-DHT can be converted into a series of reduced one-dimensional DHTs. Compared to other fast algorithms, the proposed one substantially reduces the overall Computational complexity and has a simple Computational Structure.
Vladimir Britanak - One of the best experts on this subject based on the ideXlab platform.
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New Recursive Fast Radix-2 Algorithm for the Modulated Complex Lapped Transform
IEEE Transactions on Signal Processing, 2012Co-Authors: Vladimir BritanakAbstract:A new recursive fast radix-2 algorithm for an efficient computation of the modulated complex lapped transform (MCLT) is presented. Based on a new proposed alternative recursive sparse matrix factorization for the MDCT (modified discrete cosine transform) matrix and a relation between the MDCT and the MDST (modified discrete sine transform), firstly a new recursive fast radix-2 MDST algorithm is derived. The corresponding fast MDCT and MDST Computational Structures are regular and complementary to each other. Consequently, this fact enables us by their composition to construct a fast MCLT Computational Structure representing the fast recursive radix-2 MCLT algorithm. The fast MCLT Computational Structure is regular and all its stages may be realized in parallel. Combining the proposed fast radix-2 MCLT algorithm with an existing generalized fast mixed-radix MDCT algorithm defined for the composite lengths N = 2 × qm, m ≥ 2, where q is an odd positive integer, we can compute the MCLT for the composite lengths N = 2n × qm, n, m ≥ 2, thus supporting a wider range of transform sizes compared to existing fast MCLT algorithms.
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Fast Computational Structures for an efficient implementation of the complete TDAC analysis/synthesis MDCT/MDST filter banks
Signal Processing, 2009Co-Authors: Vladimir Britanak, Huibert J. Lincklaen ArriënsAbstract:A new fast Computational Structure identical both for the forward and backward modified discrete cosine/sine transform (MDCT/MDST) computation is described. It is the result of a systematic construction of a fast algorithm for an efficient implementation of the complete time domain aliasing cancellation (TDAC) analysis/synthesis MDCT/MDST filter banks. It is shown that the same Computational Structure can be used both for the encoder and the decoder, thus significantly reducing design time and resources. The corresponding generalized signal flow graph is regular and defines new sparse matrix factorizations of the discrete cosine transform of type IV (DCT-IV) and MDCT/MDST matrices. The identical fast MDCT Computational Structure provides an efficient implementation of the MDCT in MPEG layer III (MP3) audio coding and the Dolby Labs AC-3 codec. All steps to derive the Computational Structure are described in detail, and to put them into perspective a comprehensive list of references classified into categories is provided covering new research results achieved in the time period 1999-2008 in theoretical and practical developments of TDAC analysis/synthesis MDCT/MDST filter banks (general mathematical, symmetry and special properties, fast MDCT/MDST algorithms and efficient software/hardware implementations of the MDCT in MP3).
J.c. Helton - One of the best experts on this subject based on the ideXlab platform.
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Winter Simulation Conference - Computational Structure of a performance assessment involving stochastic and subjective uncertainty
Proceedings of the 28th conference on Winter simulation - WSC '96, 1996Co-Authors: J.c. HeltonAbstract:A recent performance assessment for the Waste Isolation Pilot Plant (WIPP), which is being developed by the U.S. Department of Energy for the geologic disposal of transuranic waste, is used to illustrate the Computational Structure of a large analysis that maintains a separation between stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty. In this analysis, stochastic uncertainty arises from the many possible disruptions that could occur over the 10,000 yr regulatory period that applies to the WIPP, and subjective uncertainty arises from the imprecision with which many of the quantities required in the analysis are known. Important parts of the Computational Structure are (1) the use of Latin hyper cube sampling to incorporate the effects of subjective uncertainty, (2) the use of Monte Carlo (i.e., random) sampling to incorporate the effects of stochastic uncertainty, and (3) the efficient use of the necessarily limited number of mechanistic calculations that can be performed to support the analysis.
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Computational Structure of a performance assessment involving stochastic and subjective uncertainty
Proceedings Winter Simulation Conference, 1996Co-Authors: J.c. HeltonAbstract:A recent performance assessment for the Waste Isolation Pilot Plant (WIPP), which is being developed by the U.S. Department of Energy for the geologic disposal of transuranic waste, is used to illustrate the Computational Structure of a large analysis that maintains a separation between stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty. In this analysis, stochastic uncertainty arises from the many possible disruptions that could occur over the 10,000 yr regulatory period that applies to the WIPP, and subjective uncertainty arises from the imprecision with which many of the quantities required in the analysis are known. Important parts of the Computational Structure are (1) the use of Latin hyper cube sampling to incorporate the effects of subjective uncertainty, (2) the use of Monte Carlo (i.e., random) sampling to incorporate the effects of stochastic uncertainty, and (3) the efficient use of the necessarily limited number of mechanistic calculations that can be performed to support the analysis.
