Research and applications of blind signal separation based on kurtosis;

Most algorithms for blind signal separation(BSS) have poor performance in a noisy back-ground.

In recent years,blind signal separation(BSS) has already become a hot field of signal processing and neural network.

A High-capacity Image Watermarking Scheme Based on Blind Source Separation;

Application of blind source separation in vibration machine faults diagnosis;

Researche on vehicles tire noise detection based on blind source separation technology;

A new denoising method for ultrasonic signal based on blind source separation(BSS) is proposed.

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).

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.

Study on Forward Neural Network BSS (Blind Sources Separation) Algorithm Based on Variable Momentum Term;

Research on Electromotor Noise Fault Diagnosis Based on BSS and Wavelet Transform;

As a metric of BSS algorithms performance,the similitude coefficient is widely used.

This paper discusses Blind Source Separation (BSS) with Nonlinear PCA both theoretically and experimentally.

The Blind Source Separation (BSS) problem consists of recovery sources from the observed signals without adequate a prior knowledge.

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.