This paper presents a fast algorithm for the computation of sliding conjugate symmetric sequency-ordered complex hadamard transform (CS-SCHT). The algorithm calculates the values of window i + N/4 from those of window...
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This paper presents a fast algorithm for the computation of sliding conjugate symmetric sequency-ordered complex hadamard transform (CS-SCHT). The algorithm calculates the values of window i + N/4 from those of window, one length-N/4 Walsh hadamardtransform (WHT) and one length-N/4 Modified WHT (MWHT). The proposed algorithm requires O(N) arithmetic operations, which is more efficient than the block-based algorithms of various transforms and the sliding FFT algorithm, but less efficient than the sliding WHT algorithms. Compared to the recently proposed sliding inverse SCHT (ISCHT) algorithm, the proposed algorithm is more efficient for real input but less efficient for complex input. The applications of the sliding CS-SCHT in transform domain adaptive filtering (TDAF) to complex signal channel equalization and real speech signal acoustic echo cancellation are also provided.
A fast algorithm based on the gray code kernel (GCK) for computing the conjugate symmetric sequency-ordered complex hadamard transform (CS-SCHT) in a sliding window is presented. The proposed algorithm computes the cu...
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A fast algorithm based on the gray code kernel (GCK) for computing the conjugate symmetric sequency-ordered complex hadamard transform (CS-SCHT) in a sliding window is presented. The proposed algorithm computes the current projection value from the previously computed ones. In order to obtain the peculiar computation order of the projection values, we construct the CS-SCHT matrix tree and also introduce the alpha-related concept. The properties of the elements of the CS-SCHT matrix are also given for deriving the GCK sliding CS-SCHT algorithm. The proposed algorithm only needs N/2+log(2)N - 2 (or log(2)N - 1) multiplications with j and 4N - 2 (or 2N - 1) real additions for complex (or real) input data, which is more efficient than the block-based CS-SCHT and other existing sliding complextransform algorithms, such as the radix-4 sliding CS-SCHT algorithm, sliding FFT algorithm, and sliding DFT algorithm. A comparison of the proposed algorithm with other sliding transforms in terms of computation time is also presented to validate the theoretical results.
In this paper, an efficient algorithm for fast computation of the conjugate symmetric sequency-ordered complex hadamard transform (CS-SCHT) of any length that is a power of two is proposed using the Kronecker product....
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ISBN:
(纸本)9781424494743
In this paper, an efficient algorithm for fast computation of the conjugate symmetric sequency-ordered complex hadamard transform (CS-SCHT) of any length that is a power of two is proposed using the Kronecker product. Since the CS-SCHT matrix is factored into a product of sparse matrices, the resulting structure for the algorithm is very attractive for implementation and similar to that of the well-known Walsh-hadamardtransform, except for some multiplications by -1 or (-root-1). It is shown that the proposed N-point complex-valued CS-SCHT algorithm requires Nlog(2)(N) complex additions/subtractions and (N/2 - 1) multiplications by (-root-1)
conjugate symmetric sequency-ordered complex hadamard transform (CS-SCHT) is a new version of sequency-orderedcomplexhadamardtransform. CS-SCHT is dyadic shift invariant and the spectrum has the conjugate symmetry ...
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ISBN:
(纸本)9781467382670
conjugate symmetric sequency-ordered complex hadamard transform (CS-SCHT) is a new version of sequency-orderedcomplexhadamardtransform. CS-SCHT is dyadic shift invariant and the spectrum has the conjugate symmetry property for real signals. This transform is very suitable to derive new shape descriptor because of its excellent properties. In this paper, CS-SCHT based shape descriptor (CS-SCHD) is proposed for image retrieval. In this method each sampled shape contour is expressed using a combined real signature which captures both local and global contour information. And then CS-SCHT is applied to the signature. The CS-SCHD is formed by the resulting transform coefficients to describe shape features. The image retrieval performance of the proposed descriptor is evaluated on the standard MPEG-7 shape database using standard measurement, and compared with three other transform based descriptors. The experimental results demonstrate that the proposed CS-SCHD reaches the highest precision at the same recall value among these descriptors, and show the effectiveness of the CS-SCHD.
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