signal separation

In this paper, we present a novel application of signal separation ( BSS ) in wireless digital communication.

本文提出了基于神经网络的盲信号分离在数字无线通信中的一种应用.

Independent Component Analysis ( ICA ) is a new way for signal separation.

独立分量分析 ( ICA ) 是一种新近发展起来的信号分离方法.

To the signal from the detector, automatic separation of pneumatic components.

由探伤仪给信号, 气动元件自动分离.

Application of Blind Signal Separation Method in Analysis of Voltage Flicker

盲信号分离在电压闪变分析中的应用

This paper definites a measurement method to describe the signal separation state. After detailed analyzing relevant fixed step-size and variable step-size EASI algorithms, a new self-adaptive step-size EASI algorithm is presented.

定义了描述信号分离状态的一种测度，并在认真分析相关固定步长和变步长EASI算法的基础上，提出了一种新的步长自适应等变化自适应（EASI）算法。

Blind source separation ( BSS) is a traditional yet challenging topic in signal processing, in which the separation is performed only depends on the observed signals, without knowing source signals and the mixing channels.

盲源分离是信号处理中一个传统而又极具挑战性的课题，一般指在源信号不可测及混合系统特性未知的情况下，仅由观测信号分离出各源信号的过程。

Currently, the major domestic and foreign research is to explore a variety of separation methods and algorithms for signal separation and engineering applications.

目前，国内外主要是探讨其各种不同的分离手段和对信号分离算法及其工程应用的研究。

Blind separation of speech signals has become one of the attractive trend in the field of signal processing in recent years, owing that it has a wide application prospect in speech recognition system, computer hearing, mobile speech data communication and television and telephone conference.

因其在语音识别系统、计算机听觉、移动语音数据通信以及电视电话会议中具有广泛的应用前景，近年来日益成为信号处理领域的研究热点之一。

Wavelet Analysis and its Applications in Time-varying Filtering and Signal Separation

小波分析及其在时变滤波和信号分离中的应用

In the blind signal separation, with the crosstalk error: signal separation as a measure of the performance indicators.

在盲信号分离中，用串音误差：作为衡量信号分离的性能指标。

Signal Sampling and Transformation on Real Time Separation for Radar Repetition Period

雷达重复周期实时分选中的信号采集与变换

Single channel signal separation ( SCSS) is a fundamental and challenging research topic in signal processing field.

单通道信号分离是信号处理研究领域近年来高速发展的分支之一，是一个基本的、极富挑战性的研究课题。

The improved algorithm standard by the degree of separation, change its step size through adaptive changes in momentum factor adaptively, and thus able to improve blind source separation performance of the signal.

算法以分离度为基准，通过动量因子的自适应变化来自适应改变步长，从而能够更好的改进盲源分离后信号的性能。

A novel simplified mixing model ( SMM) is proposed for audio blind signal separation ( ABSS).

本文针对语音盲信号分离问题，提出了一种新的简化混合模型。

Some blind signal separation algorithms estimate the probability density function of the sources, with which then calculate the score function.

有些算法先估计信号概率密度，进而估计出评价函数，但是算法的复杂度高。

Then the receiving end signal separation, using the combined model incentive hair and UCA-ESPRIT algorithm for target azimuth and pitching Angle relationship.

然后对接收端信号进行分离，利用联合模式激励发和UCA-ESPRIT算法来进行目标的方位角和俯仰角度的关系。

Experiment research of a feedforward neural network for blind signal separation

前馈神经网络盲信号分离的实验研究

On Blind Signal Separation and Its Application to Process of Brain Wave

盲源分离技术用于脑电信号处理的探索