Vector Potential Quantization and the Quantum Vacuum

Scalar and Vector Quantization

Quantization is the process of mapping a continuous or discrete scalar or vector, produced by a source, into a set of digital symbols that can be transmitted or stored using a finite number of bits. In the case of continuous sources (with values in R or Rn) quantization must necessarily be used if the output of the source is to be communicated over a digital channel. In this case, it is, in gen...

Non-identity Learning Vector Quantization Applied to Evoked Potential Detection

This article presents a new computational intelligence technique for pattern recognition of graphic elements (e.g. event-related potential, auditory evoked potential, kcomplex, spindle) embedded in electro-encephalographic signals. More precisely, we have extended the learning vector quantization (LVQ) algorithm by Kohonen to nonidentity assignment to robustly detect evoked potentials in a nois...

Multiple Description Lattice Vector Quantization Multiple Description Lattice Vector Quantization

This thesis studies the multiple description vector quantization with lattice codebooks (MDLVQ). The design of index assignment is crucial to the performance of MDLVQ. However, to our best knowledge, none of previous index assignment algorithms for MDLVQ is optimal. In this thesis, we propose a simple linear-time index assignment algorithm for MDLVQ with any K ≥ 2 balanced descriptions. We prov...

Extension of two-stage vector quantization-lattice vector quantization

This paper is the extension of two-stage vector quantization–(spherical) lattice vector quantization (VQ–(S)LVQ) recently introduced by Pan and Fischer [1]. First, according to high resolution quantization theory, generalized vector quantization–lattice vector quantization (G-VQ–LVQ) is formulated in order to release the constraint of the spherical boundary for the second-stage lattice vector q...

Vector Quantization for Image Compression-Concept Quantization