common spatial pattern (csp) is a method commonly used to enhance the effects of event‑related desynchronization and event‑related synchronization present in multichannel electroencephalogram‑based brain‑computer interface (bci) systems. in the present study, a novel csp sub‑band feature selection has been proposed based on the discriminative information of the features. besides, a distinction ...

in 1997, fang proposed the concept of boundedness of $l$-fuzzy setsin $l$-topological vector spaces. since then, this concept has beenwidely accepted and adopted in the literature. in this paper,several characterizations of bounded $l$-fuzzy sets in$l$-topological vector spaces are obtained and some properties ofbounded $l$-fuzzy sets are investigated.

We consider images of boar spermatozoa obtained with an optical phase-contrast microscope. Our goal is to automatically classify single sperm cells as acrosome-intact (class 1) or acrosome-reacted (class 2). Such classification is important for the estimation of the fertilization potential of a sperm sample for artificial insemination. We segment the sperm heads and compute a feature vector for...

This paper presents a two-stage handwriting recognizer for classification of isolated characters that exploits explicit knowledge on characters’ shapes and execution plans. The first stage performs prototype extraction of the training data using a Fuzzy ARTMAP based method. These prototypes are able to improve the performance of the second stage consisting of LVQ codebooks by means of providing...

This paper presents a multiresolution adaptive vector quantization and perceptual based multiview image coding scheme. It decorrelates the input views into a number of subbands using a lifting based wavelet transform. The coefficients in the same subbands of different views are divided into vectors and then joined together. The resulting vectors are then vector quantized using an adaptive vecto...

Very fast tree-structured vector quantization employs scalar quantization decisions at each level, but chooses the dimension on which to quantize based on the coordinate direction of maximum variance. Because the quantization is scalar, searches are no more complex than scalar quantization − providing significant improvement in complexity over full-searched or even tree-structured vector quanti...

This thesis is an investigation of robust vector quantization, with the purpose of providing a system for the application of data compression and speech enhancement. Vector quantization is widely used in data compression systems. However, the performance of these systems will degrade in a noisy environment. The proposed robust vector quantization system solves the problem of optimal quantizatio...

We present a new Trellis Coded Vector Residual Quantizer (TCVRQ) that combines trellis coding and vector residual quantization. We introduce new methods for computing quantization levels and experimentally analyze the performances of our TCVRQ in the case of speech coding at very low bit rates. The results obtained show that transparent quantization of Linear Prediction (LP) parameters can be p...