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Titlebook: Algorithms for Discrete Fourier Transform and Convolution; R. Tolimieri,Myoung An,Chao Lu,C. S. Burrus (Profe Book 19891st edition Springe

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Multiplicative Characters and the FFT, .-decimated and .. -periodic functions on .. with . = ../.. and proved that . where . is the orthogonal complement of .0 in .(..). The space .0 and . are invariant under the action of the Fourier transform . of ... The action of . on .0 was described in the preceeding chapter. We will now take up t
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Springer Science+Business Media New York 1989
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https://doi.org/10.1007/978-3-658-20787-8Tensor product offers a natural language for expressing digital signal processing(DSP) algorithms. In this chapter, we define the tensor product and derive several important tensor product identities.
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https://doi.org/10.1007/978-3-531-91713-9The ring structure of . provides important tools for gaining deep insights into algorithm design. The fundamental partition of the indexing set .., a major step in the Rader-Winograd FT algorithm of the preceeding chapter, was based on the unit group .(..). We will now examine how the ideal theory of the ring . can be used for algorithm design.
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Introduction to Abstract Algebra,In this and the next chapters, we present several mathematical results needed to design the algorithms of the text. We assume that the reader has some knowledge of groups, rings and vector spaces but no extensive knowledge is required. Instead, we focus on those mathematical objects which will be used repeatedly in this text.
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Tensor Product and Stride Permutation,Tensor product offers a natural language for expressing digital signal processing(DSP) algorithms. In this chapter, we define the tensor product and derive several important tensor product identities.
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