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Classification, Parameter Estimation and State Estimation, 2nd Edition by David M. J. Tax, Dick de Ridder, Ferdinand van der Heijden, Yaobin Zou, Ming Feng, Guangzhu Xu, Bangjun Lei

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2PRTools Introduction

2.1 Motivation

Scientists should build their own instruments, or at least be able to open, investigate and understand the tools they are using. If, however, the tools are provided as a black box there should be a manual or literature available that fully explains the ins and outs. In principle, scientists should be able to create their measurement devices from scratch; otherwise the progress in science has no foundations.

In statistical pattern recognition one studies techniques for the generalization of examples to decision rules to be used for the detection and recognition of patterns in experimental data. This research area has a strong computational character, demanding a flexible use of numerical programs for data analysis as well as for the evaluation of the procedures. As still new methods are being proposed in the literature a programming platform is needed that enables a fast and flexible implementation.

Matlab® is the dominant programming language for implementing numerical computations and is widely used for algorithm development, simulation, data reduction, and testing and system evaluation. Pattern recognition is studied in almost all areas of applied science. Thereby the use of a widely available numerical toolset like Matlab® may be profitable for both the use of existing techniques as well as for the study of new algorithms. Moreover, because of its general nature in comparison with more specialized statistical environments, it offers an ...

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