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1)  BSS Encryption
盲源分离加密
2)  blind signal separation
盲源分离
1.
Research and applications of blind signal separation based on kurtosis;
基于峰度的盲源分离算法研究与应用
2.
Most algorithms for blind signal separation(BSS) have poor performance in a noisy back-ground.
噪声环境下大多数盲源分离算法性能大大降低。
3.
In recent years,blind signal separation(BSS) has already become a hot field of signal processing and neural network.
将盲源分离算法应用于雷达阵列接收信号处理,提出了一种新的盲源分离算法的性能评价标准—相关系数法。
3)  blind source separation
盲源分离
1.
A High-capacity Image Watermarking Scheme Based on Blind Source Separation;
基于盲源分离的大容量图像数字水印方案
2.
Application of blind source separation in vibration machine faults diagnosis;
盲源分离在振动机械故障诊断中的应用
3.
Researche on vehicles tire noise detection based on blind source separation technology;
盲源分离技术在车辆轮胎噪声提取中的应用
4)  Blind source separation(BSS)
盲源分离
1.
A new denoising method for ultrasonic signal based on blind source separation(BSS) is proposed.
提出一种新的基于盲源分离的超声信号去噪方法。
2.
In order to remove multiplicative noise in observation a new method for multiplicative noise reduction based on homomorphic transform and blind source separation(BSS) was proposed,using redundancy reduction of independent component analysis(ICA).
为消除乘法性观测噪声,利用独立分量分析的冗余取消特性,提出一种基于同态变换盲源分离(BSS)的消噪新方法。
3.
According to the principle of maximizing statistical independence between the estimated components formulated by high order accumulates,the blind source separation(BSS) of ICA was applied to the extended observed signal.
通过分析传统去噪方法的优缺点,引入基于独立分量分析的噪声消除方法,该方法不需要观测信号为确定性信号的前提假设,通过对加噪观测信号进行盲源分离,得到源观测信号,从而实现对噪声的消除。
5)  BSS
盲源分离
1.
Study on Forward Neural Network BSS (Blind Sources Separation) Algorithm Based on Variable Momentum Term;
对基于变动量项前馈神经网络盲源分离算法的研究
2.
Research on Electromotor Noise Fault Diagnosis Based on BSS and Wavelet Transform;
基于盲源分离和小波分析的电机声频故障诊断研究
3.
As a metric of BSS algorithms performance,the similitude coefficient is widely used.
为了评价盲源分离(BSS)效果,目前普遍采用的检验指标是相似系数。
6)  blind source separation (BSS)
盲源分离
1.
This paper discusses Blind Source Separation (BSS) with Nonlinear PCA both theoretically and experimentally.
主要讨论了基于非线性主分量分析(NPCA)的盲源分离,从理论与实验2个方面详细分析了算法的特性与效果。
2.
The Blind Source Separation (BSS) problem consists of recovery sources from the observed signals without adequate a prior knowledge.
盲源分离(BSS)问题是在缺少先验知识的情况下,从接收到的观测信号中恢复统计独立的源信号。
3.
In this paper, we show the basic mathematic model and separated algorithms of blind source separation (BSS)/ independent component analysis (ICA) firstly, we discuss in more detail uniqueness issues about the nonlinear BSS/ICA problems.
本文主要阐述了非线性盲源分离(BSS)/独立成分分析(ICA)模型的基本数学原理、分离算法、算法性能及其应用。
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