Adaptive Weight Texture Segmentation Based on Criterion of Separability;

Face recognition based on adaptive weight and local singular value decomposition

In order to solve the above problems,this paper proposes a mirrored adaptive weight(MAW)algorithm,which calculates cost vector based on adaptive neighbor weight error criterion(ANWMAE).

Using computer formidable value computation and information-handling capacity,after eliminating fail data,data fusion method based on the adaptive weighting is used.

An adaptive weighting algorithm is proposed based on the adaptive null beamforming technology,which can be used for forming arbitrary sidelobe shape beam pattern for arbitrary structure arrays,considering the effect of element directivity at the same time.

Based on the use of adaptive weighting algorithm for main lobe controlling technique,the shape of beam pattern is changed by introducing some virtual interferers in the side lobe domain and adjusting the strength of interferers at the same time.

The validity,accuracy and actual time of the algorithm for batched-estimation,self-adaptive weighting and variance-estimation are studied in multi-sensors data fusion.

In this work ,a new fast adaptive weighted median filter(FAWMF) is proposed for improving the performance of median-based filters In this algorithm,noise detection is used to determine impulse noise and the degree of the noise interference .

A method of grey superior analysis based on adaptive weighted data fusion is used to process the multi-sensors data.

The paper proposes a new adaptive weighted average filtering algorithm based on the feature of local spatial pixels that removes the ‘salt & pepper’ noise.