Ebook: Foundations of Computational Intelligence Volume 5: Function Approximation and Classification
- Tags: Appl.Mathematics/Computational Methods of Engineering, Artificial Intelligence (incl. Robotics)
- Series: Studies in Computational Intelligence 205
- Year: 2009
- Publisher: Springer-Verlag Berlin Heidelberg
- Edition: 1
- Language: English
- pdf
Approximation theory is that area of analysis which is concerned with the ability to approximate functions by simpler and more easily calculated functions. It is an area which, like many other fields of analysis, has its primary roots in the mathematics.The need for function approximation and classification arises in many branches of applied mathematics, computer science and data mining in particular.
This edited volume comprises of 14 chapters, including several overview Chapters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of function approximation and classification. Besides research articles and expository papers on theory and algorithms of function approximation and classification, papers on numerical experiments and real world applications were also encouraged.
The Volume is divided into 2 parts: Part-I: Function Approximation and Classification – Theoretical Foundations and Part-II: Function Approximation and Classification – Success Stories and Real World Applications.
Approximation theory is that area of analysis which is concerned with the ability to approximate functions by simpler and more easily calculated functions. It is an area which, like many other fields of analysis, has its primary roots in the mathematics.The need for function approximation and classification arises in many branches of applied mathematics, computer science and data mining in particular.
This edited volume comprises of 14 chapters, including several overview Chapters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of function approximation and classification. Besides research articles and expository papers on theory and algorithms of function approximation and classification, papers on numerical experiments and real world applications were also encouraged.
The Volume is divided into 2 parts: Part-I: Function Approximation and Classification – Theoretical Foundations and Part-II: Function Approximation and Classification – Success Stories and Real World Applications.