用于奇異值分解的全并行神經(jīng)網(wǎng)絡(luò)
A NEW TOTAL PARALLEL NEURAL NETWORK FOR SVD
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摘要: 本文提出一個(gè)實(shí)時(shí)奇異值分解(SVD)的全并行神經(jīng)網(wǎng)絡(luò),給出并證明了它的有界性定理和穩(wěn)定性定理,同時(shí)給出一個(gè)模擬例子。理論和模擬結(jié)果都說(shuō)明所提出的神經(jīng)網(wǎng)絡(luò)對(duì)于SVD是有效的。Abstract: The paper presents a total parallell neural network for real-tune computation of SVD. Its boundedness and stability of the dynamical system are studied. Computer simulation is also given. The results of the theoretical analysis and simulation illustate that this neural network is feasible and efficient for SVD.
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