Fast Searching Algorithm for Vector Quantization Based on Subvector Technique
نویسندگان
چکیده
منابع مشابه
A fast encoding algorithm for vector quantization using dynamic subvector technique
The encoding of vector quantization (VQ) needs expensive computation for searching the closet codeword to the input vectors. In order to reduce computation burden, Pan et al. have developed an efficient full-search-equivalent algorithm by using the characteristics of the sums and variances of a vector and its two fixed subvectors recently. However, some computational redundancies still exist in...
متن کاملA fast nearest neighbor search algorithm based on vector quantization
In this article, we propose a new fast nearest neighbor search algorithm, based on vector quantization. Like many other branch and bound search algorithms [1, 10], a preprocessing recursively partitions the data set into disjointed subsets until the number of points in each part is small enough. In doing so, a search-tree data structure is built. This preliminary recursive data-set partition is...
متن کاملFast Encoding Algorithm for Vector Quantization
In this paper, we present a new and fast encoding algorithm (FEA) for vector quantization. The magnitude (sum of the components of a vector) feature of the vectors is used in this algorithm to improve the efficiency of searching. Sorting of the magnitude values enhances the searching. As the values are sorted, the searching can be terminated in advance to reduce the time needed to locate the re...
متن کاملFast Learning Algorithm for Fuzzy Inference Systems using Vector Quantization
It is known that learning methods of fuzzy inference systems using vector quantization (VQ) and steepest descend method (SDM) are superior in terms of the number of rules. However, they need a great deal of learning time. The cause could be that both of VQ and SDM perform only local searches. On the other hand, it has been shown that a learning method of radial basis function (RBF) networks usi...
متن کاملAlgorithms for Fast Vector Quantization∗
Nearest neighbor searching is an important geometric subproblem in vector quantization. Existing studies have shown that the difficulty of solving this problem efficiently grows rapidly with dimension. Indeed, existing approaches on unstructured codebooks in dimension 16 are little better than brute-force search. We show that if one is willing to relax the requirement of finding the true neares...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2008
ISSN: 0916-8532,1745-1361
DOI: 10.1093/ietisy/e91-d.7.2035