Modeling of a time-varying dynamical system provides insights into the functions of biological neural networks and contributes to the development of next-generation neural prostheses. In this paper, we have formulated a novel sparse multiwavelet-based generalized Laguerre–Volterra (sMGLV) modeling framework to identify the time-varying neural dynamics from multiple spike train data. First, the ...

Starting from any two compactly supported d-refinable function vectors in ( L2(R) )r with multiplicity r and dilation factor d, we show that it is always possible to construct 2rd wavelet functions with compact support such that they generate a pair of dual d-wavelet frames in L2(R) and they achieve the best possible orders of vanishing moments. When all the components of the two real-valued d-...

This paper considers the classical sampling theorem in multiresolution spaces with scaling functions as interpolants. As discussed by Xia and Zhang, for an orthogonal scaling function to support such a sampling theorem, the scaling function must be cardinal (interpolating). They also showed that the only orthogonal scaling function that is both cardinal and of compact support is the Haar functi...

A complex-valued convolutional network (convnet) implements the repeated application of the following composition of three operations, recursively applying the composition to an input vector of nonnegative real numbers: (1) convolution with complex-valued vectors, followed by (2) taking the absolute value of every entry of the resulting vectors, followed by (3) local averaging. For processing r...

This paper describes a new approach for the classification of brain tissues into White Matter, Gray Matter, Cerebral Spinal Fluid, Glial Matter, Connective and MS lesion in multiple sclerosis. The proposed approach employs singular value decomposition on multiwavelet transformed images. Single level multiwavelet transformation decomposes images into 16 subbands, and each subband represents the ...

To develop Human-centric Driver Assistance Systems (HDAS) for automatic understanding and charactering of driver behaviors, an efficient feature extraction of driving postures based on Geronimo–Hardin–Massopust (GHM) multiwavelet transform is proposed, and Multilayer Perceptron (MLP) classifiers with three layers are then exploited in order to recognize four pre-defined classes of driving postu...

Recently, the wavelet transform has emerged as a cutting edge technology within the field of image compression research. Wavelet methods involve overlapping transforms with varying-length basis functions. This overlapping nature of the transform alleviates blocking artifacts, while the multi-resolution character of the wavelet decomposition leads to superior energy compaction and perceptual qua...

In this paper we propose an extension to the work of Lischinski et al [1] on combining hierarchical radiosity method and discontinuity meshing. The extension proposed here supports higher order radiosity function at the es timation s tep itself. We have carried out this extension using M ultiWavelet basis function s. Unlike th e multi-wavelet radiosity work of Gortler et al [2] which uses reg u...