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H. Murakami - One of the best experts on this subject based on the ideXlab platform.
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Generalization of the Cyclic Convolution system and its applications
2000 IEEE International Conference on Acoustics Speech and Signal Processing. Proceedings (Cat. No.00CH37100), 2000Co-Authors: H. MurakamiAbstract:This paper introduces a generalized Cyclic Convolution which can be implemented via the conventional Cyclic Convolution system by the discrete Fourier transform (DFT) with pre-multiplication for the input and post-multiplication for the output. The generalized Cyclic Convolution is applied for computing a negaCyclic Convolution. Comparison shows that the proposed implementation is more efficient and simpler in structure than other methods. The generalized Cyclic Convolution is also applied for the linear Convolution by the modified Fermat number transform.
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Computation of negaCyclic Convolution and modified Fermat transform
2000 TENCON Proceedings. Intelligent Systems and Technologies for the New Millennium (Cat. No.00CH37119), 2000Co-Authors: H. MurakamiAbstract:This paper introduces a generalized Cyclic Convolution which can be implemented via the conventional Cyclic Convolution system by the discrete Fourier transform (DFT) with pre-multiplication for the input and post-multiplication for the output. The generalized Cyclic Convolution is applied for computing a negaCyclic Convolution. Comparison shows that the proposed implementation is more efficient and simpler in structure than other methods. The generalized Cyclic Convolution is also applied for the linear Convolution by the modified Fermat number transform.
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Block sampling rate conversion systems using real-valued fast Cyclic Convolution algorithms
IEEE Transactions on Signal Processing, 1997Co-Authors: H. MurakamiAbstract:The real-valued transform is related to the polyphase decomposition of a sequence. This observation is applied for deriving sampling rate conversion systems that are implemented by the real-valued fast Cyclic Convolution algorithms. The systems include interpolation by an integer factor, decimation by an integer factor, and sampling rate conversion by a rational factor. The proposed implementations are useful when the signals and impulse responses of filters are restricted to be real.
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real valued fast discrete fourier transform and Cyclic Convolution algorithms of highly composite even length
International Conference on Acoustics Speech and Signal Processing, 1996Co-Authors: H. MurakamiAbstract:This paper introduces a new recursive factorization of the polynomial, 1-z/sup N/, over the real numbers when N is an even composite integer. The recursive factorization is applied for efficient computation of the discrete Fourier transform (DFT) and the Cyclic Convolution of real sequences with highly composite even length.
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ICASSP - Generalization of the Cyclic Convolution system and its applications
2000 IEEE International Conference on Acoustics Speech and Signal Processing. Proceedings (Cat. No.00CH37100), 1Co-Authors: H. MurakamiAbstract:This paper introduces a generalized Cyclic Convolution which can be implemented via the conventional Cyclic Convolution system by the discrete Fourier transform (DFT) with pre-multiplication for the input and post-multiplication for the output. The generalized Cyclic Convolution is applied for computing a negaCyclic Convolution. Comparison shows that the proposed implementation is more efficient and simpler in structure than other methods. The generalized Cyclic Convolution is also applied for the linear Convolution by the modified Fermat number transform.
Stefan Kuhl - One of the best experts on this subject based on the ideXlab platform.
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a joint perspective of periodically excited efficient nlms algorithm and inverse Cyclic Convolution
International Conference on Acoustics Speech and Signal Processing, 2018Co-Authors: Stefan Kuhl, Christiane Antweiler, Sebastian Nagel, Tobias Kabzinski, Peter JaxAbstract:Research in static and time-variant system identification has brought up a broad variety of identification algorithms. In acoustics, e.g., static measurements of transfer functions are commonly conducted using Inverse Cyclic Convolution (ICC) with Exponential Sweep excitation. Identification and tracking of time-variant systems, however, often employ adaptive filter algorithms, such as the Normalized Least Mean Square (NLMS) algorithm. An interesting implementation variant is the so-called Efficient NLMS (eNLMS) algorithm for arbitrary periodic excitation. ICC and the eNLMS algorithm originate from different fields and have so far evolved independently. This paper bridges the gap using a theoretical analysis of both algorithms to prove that they can be transferred into each other. This understanding provides a joint perspective, such that know-how from both fields can be combined to further optimize the system identification process.
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ICASSP - A Joint Perspective of Periodically Excited Efficient NLMS Algorithm and Inverse Cyclic Convolution
2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2018Co-Authors: Stefan Kuhl, Christiane Antweiler, Sebastian Nagel, Tobias Kabzinski, Peter JaxAbstract:Research in static and time-variant system identification has brought up a broad variety of identification algorithms. In acoustics, e.g., static measurements of transfer functions are commonly conducted using Inverse Cyclic Convolution (ICC) with Exponential Sweep excitation. Identification and tracking of time-variant systems, however, often employ adaptive filter algorithms, such as the Normalized Least Mean Square (NLMS) algorithm. An interesting implementation variant is the so-called Efficient NLMS (eNLMS) algorithm for arbitrary periodic excitation. ICC and the eNLMS algorithm originate from different fields and have so far evolved independently. This paper bridges the gap using a theoretical analysis of both algorithms to prove that they can be transferred into each other. This understanding provides a joint perspective, such that know-how from both fields can be combined to further optimize the system identification process.
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system identification with perfect sequence excitation efficient nlms vs inverse Cyclic Convolution
ITG Symposium of Speech Communication, 2014Co-Authors: Christiane Antweiler, Stefan Kuhl, Bastian Sauert, Peter VaryAbstract:Linear transmission systems are often characterized by their impulse responses. A simple and fast approach to acquire these impulse responses is the normalized leastmean-square (NLMS) algorithm in combination with a perfect sequence excitation. It is not only applicable to static impulse response measurements, but has been optimized especially for the tracking of time varying linear systems. In this paper, different implementation strategies of the perfect sequence excited NLMS algorithm, namely the efficient NLMS and the inverse Cyclic Convolution algorithm, are discussed and compared in terms of performance, complexity, and applicability. As a main result it is shown that for certain conditions all algorithmic variants can be transferred to each other.
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ITG Symposium on Speech Communication - System Identification with Perfect Sequence Excitation - Efficient NLMS vs. Inverse Cyclic Convolution.
2014Co-Authors: Christiane Antweiler, Stefan Kuhl, Bastian Sauert, Peter VaryAbstract:Linear transmission systems are often characterized by their impulse responses. A simple and fast approach to acquire these impulse responses is the normalized leastmean-square (NLMS) algorithm in combination with a perfect sequence excitation. It is not only applicable to static impulse response measurements, but has been optimized especially for the tracking of time varying linear systems. In this paper, different implementation strategies of the perfect sequence excited NLMS algorithm, namely the efficient NLMS and the inverse Cyclic Convolution algorithm, are discussed and compared in terms of performance, complexity, and applicability. As a main result it is shown that for certain conditions all algorithmic variants can be transferred to each other.
Pramod Kumar Meher - One of the best experts on this subject based on the ideXlab platform.
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SUBMITTED TO IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 1 Parallel and Pipelined Architectures for Cyclic Convolution by Block Circulant Formulation using Low-Complexity Short-Length Algorithms
2016Co-Authors: Pramod Kumar Meher, Senior MemberAbstract:Abstract—Fully-pipelined parallel architectures are derived for high-throughput and reduced-hardware realization of prime-factor Cyclic Convolution using hardware-efficient modules for short-length rectangular transform (RT). Moreover, a new ap-proach is proposed for the computation of block pseudo-Cyclic Convolution using a block Cyclic Convolution of equal length along with some correction terms, so that the block pseudo-Cyclic representation of Cyclic Convolution for non-prime-factor-length (N = rP, when r and P are not mutually prime) could be computed efficiently using the algorithms and architectures of short-length Cyclic Convolutions. Low-complexity algorithms are derived for efficient computation of those error terms; and overall complexities of the proposed technique are estimated for r = 2, 3, 4, 6, 8 and 9. The proposed algorithms are used further to design high-throughput and reduced-hardware structures for Cyclic Convolution where the co-factors are not relatively prime. The proposed structures for high-throughput implementation are found to offer a reduction of nearly 50 to 75 % of area-delay prod-uct over the existing structures for several Convolution lengths. Low-complexity structures for input/output addition units of short Convolution-lengths are derived and used them along with high-throughput modules for hardware-efficient realization of multi-factor Convolution which offers nearly 25 to 75 % reduction of area-delay complexity over the existing structures for various non-prime-factor Convolution lengths. Index Terms—Cyclic Convolution, block Cyclic Convolution, pseudo-Cyclic Convolution, systolic array, VLSI. I
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Efficient systolization of Cyclic Convolution for systolic implementation of sinusoidal transforms
2008 International Conference on Application-Specific Systems Architectures and Processors, 2008Co-Authors: Pramod Kumar MeherAbstract:This paper presents an algorithm to convert composite-length Cyclic Convolution into a block Cyclic Convolution sum of small matrix-vector products, even if the co-factors of Convolution-length are not mutually prime. It is shown that by using optimal short-length Convolution algorithms, the block-Convolution could be computed from a few short-length Cyclic and Cyclic-like Convolutions, when one of the co-factors belongs to {2, 3, 4, 6, 8}. A generalized systolic array is derived for Cyclic-like Convolution, and used that for the computation of long-length Convolutions. The proposed structure for Convolution-length N= 2L involves nearly the same hardware and half the time-complexity as the direct implementation; and the structure for N= 4L involves sime12.5% more hardware and one-fourth the time-complexity of the latter. The structures for N=2L and N=4L, respectively, have the same and sime12.5% less area-time complexity as the corresponding existing prime-factor systolic structures, but unlike the latter type, do not involve complex input/output mapping; and could be used even if the co-factors of Convolution-length are not relatively prime.
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Parallel and Pipelined Architectures for Cyclic Convolution by Block Circulant Formulation Using Low-Complexity Short-Length Algorithms
IEEE Transactions on Circuits and Systems for Video Technology, 2008Co-Authors: Pramod Kumar MeherAbstract:Fully pipelined parallel architectures are derived for high-throughput and reduced-hardware realization of prime-factor Cyclic Convolution using hardware-efficient modules for short-length rectangular transform (RT). Moreover, a new approach is proposed for the computation of block pseudoCyclic Convolution using a block Cyclic Convolution of equal length along with some correction terms, so that the block pseudoCyclic representation of Cyclic Convolution for non-prime-factor-length (N=rP , when r and P are not mutually prime) could be computed efficiently using the algorithms and architectures of short-length Cyclic Convolutions. Low-complexity algorithms are derived for efficient computation of those error terms, and overall complexities of the proposed technique are estimated for r=2, 3, 4, 6, 8 and 9. The proposed algorithms are used further to design high-throughput and reduced-hardware structures for Cyclic Convolution where the cofactors are not relatively prime. The proposed structures for high-throughput implementation are found to offer a reduction of nearly 50%-75% of area-delay product over the existing structures for several Convolution-lengths. Low-complexity structures for input/output addition units of short length Convolutions are derived and used them along with high-throughput modules for hardware-efficient realization of multifactor Convolution, which offers nearly 25%-75% reduction of area-delay complexity over the existing structures for various non-prime-factor length Convolutions.
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ASAP - Efficient systolization of Cyclic Convolution for systolic implementation of sinusoidal transforms
2008 International Conference on Application-Specific Systems Architectures and Processors, 2008Co-Authors: Pramod Kumar MeherAbstract:This paper presents an algorithm to convert composite-length Cyclic Convolution into a block Cyclic Convolution sum of small matrix-vector products, even if the co-factors of Convolution-length are not mutually prime. It is shown that by using optimal short-length Convolution algorithms, the block-Convolution could be computed from a few short-length Cyclic and Cyclic-like Convolutions, when one of the co-factors belongs to {2, 3, 4, 6, 8}. A generalized systolic array is derived for Cyclic-like Convolution, and used that for the computation of long-length Convolutions. The proposed structure for Convolution-length N= 2L involves nearly the same hardware and half the time-complexity as the direct implementation; and the structure for N= 4L involves sime12.5% more hardware and one-fourth the time-complexity of the latter. The structures for N=2L and N=4L, respectively, have the same and sime12.5% less area-time complexity as the corresponding existing prime-factor systolic structures, but unlike the latter type, do not involve complex input/output mapping; and could be used even if the co-factors of Convolution-length are not relatively prime.
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Efficient Systolization of Cyclic Convolutions Using Low-Complexity Rectangular Transform Algorithms
2007 International Symposium on Signals Circuits and Systems, 2007Co-Authors: Pramod Kumar MeherAbstract:Systolic-like modular architectures are derived for short-length Cyclic Convolution using the optimal rectangular transform (RT) algorithm. Besides, a reduced-complexity recursive formulation of 2-factor RT-based algorithm is presented for computation of Cyclic Convolution of length N = N\ x N2, where JVi and JV2 are relatively prime. The proposed recursive formulation is used further to derive simple and regular linear systolic arrays for N = 2M and N = AM, where M is any odd positive integer. It is shown that the proposed structures for N = 2M and N = AM, respectively, involve less than the half and the one-third the area-time complexity of the direct systolic implementation of Cyclic Convolution.
Martin Vetterli - One of the best experts on this subject based on the ideXlab platform.
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ICASSP - Cyclic Convolution of real sequences: Hartley versus Fourier and new schemes
ICASSP '86. IEEE International Conference on Acoustics Speech and Signal Processing, 1Co-Authors: Pierre Duhamel, Martin VetterliAbstract:Recently, new fast transforms (such as the discrete Hartley transform in particular) have been proposed which are best suited for the computation of Cyclic Convolution of real sequences. Two approaches using Fourier or Hartley transforms are first compared, showing that the recently proposed FFT algorithms for real data present a lower arithmetic complexity than the corresponding DHT-based approach. Improvements are made to both types of algorithms, leading to different trade offs between arithmetic and structural complexity. We also present a new Hartley Transform algorithm with lower arithmetic complexity than any previously published one.
Christiane Antweiler - One of the best experts on this subject based on the ideXlab platform.
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a joint perspective of periodically excited efficient nlms algorithm and inverse Cyclic Convolution
International Conference on Acoustics Speech and Signal Processing, 2018Co-Authors: Stefan Kuhl, Christiane Antweiler, Sebastian Nagel, Tobias Kabzinski, Peter JaxAbstract:Research in static and time-variant system identification has brought up a broad variety of identification algorithms. In acoustics, e.g., static measurements of transfer functions are commonly conducted using Inverse Cyclic Convolution (ICC) with Exponential Sweep excitation. Identification and tracking of time-variant systems, however, often employ adaptive filter algorithms, such as the Normalized Least Mean Square (NLMS) algorithm. An interesting implementation variant is the so-called Efficient NLMS (eNLMS) algorithm for arbitrary periodic excitation. ICC and the eNLMS algorithm originate from different fields and have so far evolved independently. This paper bridges the gap using a theoretical analysis of both algorithms to prove that they can be transferred into each other. This understanding provides a joint perspective, such that know-how from both fields can be combined to further optimize the system identification process.
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ICASSP - A Joint Perspective of Periodically Excited Efficient NLMS Algorithm and Inverse Cyclic Convolution
2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2018Co-Authors: Stefan Kuhl, Christiane Antweiler, Sebastian Nagel, Tobias Kabzinski, Peter JaxAbstract:Research in static and time-variant system identification has brought up a broad variety of identification algorithms. In acoustics, e.g., static measurements of transfer functions are commonly conducted using Inverse Cyclic Convolution (ICC) with Exponential Sweep excitation. Identification and tracking of time-variant systems, however, often employ adaptive filter algorithms, such as the Normalized Least Mean Square (NLMS) algorithm. An interesting implementation variant is the so-called Efficient NLMS (eNLMS) algorithm for arbitrary periodic excitation. ICC and the eNLMS algorithm originate from different fields and have so far evolved independently. This paper bridges the gap using a theoretical analysis of both algorithms to prove that they can be transferred into each other. This understanding provides a joint perspective, such that know-how from both fields can be combined to further optimize the system identification process.
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system identification with perfect sequence excitation efficient nlms vs inverse Cyclic Convolution
ITG Symposium of Speech Communication, 2014Co-Authors: Christiane Antweiler, Stefan Kuhl, Bastian Sauert, Peter VaryAbstract:Linear transmission systems are often characterized by their impulse responses. A simple and fast approach to acquire these impulse responses is the normalized leastmean-square (NLMS) algorithm in combination with a perfect sequence excitation. It is not only applicable to static impulse response measurements, but has been optimized especially for the tracking of time varying linear systems. In this paper, different implementation strategies of the perfect sequence excited NLMS algorithm, namely the efficient NLMS and the inverse Cyclic Convolution algorithm, are discussed and compared in terms of performance, complexity, and applicability. As a main result it is shown that for certain conditions all algorithmic variants can be transferred to each other.
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ITG Symposium on Speech Communication - System Identification with Perfect Sequence Excitation - Efficient NLMS vs. Inverse Cyclic Convolution.
2014Co-Authors: Christiane Antweiler, Stefan Kuhl, Bastian Sauert, Peter VaryAbstract:Linear transmission systems are often characterized by their impulse responses. A simple and fast approach to acquire these impulse responses is the normalized leastmean-square (NLMS) algorithm in combination with a perfect sequence excitation. It is not only applicable to static impulse response measurements, but has been optimized especially for the tracking of time varying linear systems. In this paper, different implementation strategies of the perfect sequence excited NLMS algorithm, namely the efficient NLMS and the inverse Cyclic Convolution algorithm, are discussed and compared in terms of performance, complexity, and applicability. As a main result it is shown that for certain conditions all algorithmic variants can be transferred to each other.
