基于时频非负矩阵分解和S形基归一化深度神经网络的单通道源分离

IF 1.7 4区工程技术 Q2 COMPUTER SCIENCE, THEORY & METHODS

Multidimensional Systems and Signal Processing Pub Date : 2022-05-05 DOI:10.1007/s11045-022-00830-2

Y. V. Koteswararao, C. R. Rao

引用次数: 1

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Single channel source separation using time–frequency non-negative matrix factorization and sigmoid base normalization deep neural networks

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Single channel source separation using time–frequency non-negative matrix factorization and sigmoid base normalization deep neural networks

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来源期刊

Multidimensional Systems and Signal Processing 工程技术-工程：电子与电气

CiteScore

5.60

自引率

8.00%

发文量

审稿时长

11.7 months

期刊介绍： Multidimensional Systems and Signal Processing publishes research and selective surveys papers ranging from the fundamentals to important new findings. The journal responds to and provides a solution to the widely scattered nature of publications in this area, offering unity of theme, reduced duplication of effort, and greatly enhanced communication among researchers and practitioners in the field. A partial list of topics addressed in the journal includes multidimensional control systems design and implementation; multidimensional stability and realization theory; prediction and filtering of multidimensional processes; Spatial-temporal signal processing; multidimensional filters and filter-banks; array signal processing; and applications of multidimensional systems and signal processing to areas such as healthcare and 3-D imaging techniques.