Up to a few years ago, the approaches taken to check whether a hardware component works as expected could be classi ed under one of two styles: hardware engineers in the industry would tend to exclusively use simulation to (empirically) test their c
This e-book is devoted to global optimization algorithms, which are methods to find opti- mal solutions for given problems. It especially focuses on Evolutionary Computation by dis- cussing evolutionary algorithms, genetic algorithms, Genetic Progra
Probabilistic subspace mixture models, as proposed over the last few years, are interesting methods for learning image manifolds, i.e. nonlinear subspaces of spaces in which images are represented as vectors by their grey-values. Their lack of a glo
This book is a graduate-level textbook on data structures. A data structure is a method1 to realize a set of operations on some data. The classical example is to keep track of a set of items, the items identified by key values, so that we can insert
Abstract Support vector machine (SVM) is a popular technique for classi cation. However, beginners who are not familiar with SVM often get unsatisfactory results since they miss some easy but signi cant steps. In this guide, we propose a simple proc
演化硬件在声纳识别中的应用 Abstract: An evolvable hardware (EHW) system for high-speed sona return classification has been proposed. The system demonstrates an average accuracy of 91.4% on a sonar spectrum data set. This is bette than a feed-forward neural netwo
David J. C. MacKay's book. The textbook used for the information theory course in Cambridge University. Also an excellent book for machine learning. The special feature of this book is it reveals the relationship between information theory and machi
Abstract—This paper introduces a multilinear principal com- ponent analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern recognition applications, such as 2-D/3-D images and video seq
A common method for real-time segmentation of moving regions in image sequences involves “back- ground subtraction,” or thresholding the error between an estimate of the image without moving objects and the current image. The numerous approaches to
This book presents the basic tools of modern analysis within the context of what might be called the fundamental problem of operator theory: to calculate spectra of specific operators on infinite-dimensional spaces, especially operators on Hilbert spa
Various black-box methods for the generation of test cases have been proposed in the literature. Many of these methods, including the category-partition method and the classi cation-tree method, follow the approach of partition testing, in which the
