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Statistical learning theory was introduced in the late 1960's. Until the 1990's it was a purely theoretical analysis of the problem of function estimation from a given collection of data. In the middle of the 1990's new ...

Subjects / keywords: Computer science; Mathematics; Set theory; Problems, exercises, etc; Algorithms; Logic, Symbolic and mathematical; Problems and exercises; Electronic books

We introduce space-time block coding, a new paradigm for communication over Rayleigh fading channels using multiple transmit antennas. Data is encoded using a space-time block code and the encoded data is split into n st...

A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data. Highly applicable to a ...

SIR 97 is the integration of two programs, SIR 92 and CAOS , the first devoted to the solution of crystal structures by direct methods, the second to refinement via least-squares–Fourier procedures. Several new feature...

Subjects / keywords: Wavelet; Wavelet packet decomposition; Second-generation wavelet transform; Discrete wavelet transform; Zoom; Stationary wavelet transform; Wavelet transform; Harmonic wavelet transform; Algorithm; Computer science; Math...

Abstract We investigate the use of multiple transmitting and/or receiving antennas for single user communications over the additive Gaussian channel with and without fading. We derive formulas for the capacities and erro...

Subjects / keywords: Engineering optimization; Computer science; Optimization problem; Industrial engineering; Operations research; Management science; Engineering; Algorithm

Subjects / keywords: TREMBLAY, JEAN-PAUL; MCGRAW-HILL; 005.113 T789in

Subjects / keywords: Python (Computer program language); Data structures (Computer science); Computer algorithms

Subjects / keywords: Text processing (Computer science); Genetic algorithms; Computational linguistics

Subjects / keywords: Computer algorithms; Databases; Data structures (Computer science); Structured programming

Abstract The last decade witnessed a great evolution on the fields of computer science, artificial intelligence, communication and data transmission. This evolution draw the attention of specialists to design a modern cr...

This book presents the fundamentals of discrete-time signals, systems, algorithms and applications for students in electrical engineering or computer science. It covers both time-domain and frequency- domain methods for ...

This book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populat...

Several algorithms have been described in the literature for protein identification by searching a sequence database using mass spectrometry data. In some approaches, the experimental data are peptide molecular weights f...

Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Composed of simple interacting agents, this intelligence lies in the networks...

An ad-hoc network is the cooperative engagement of a collection of mobile nodes without the required intervention of any centralized access point or existing infrastructure. We present Ad-hoc On Demand Distance Vector Ro...

The network structure of a hyperlinked environment can be a rich source of information about the content of the environment, provided we have effective means for understanding it. We develop a set of algorithmic tools fo...

Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disci...