Mathematical tests about the existence and applications of PPS wavelets in function approximation problems
João Fernando Marar, Edson C. B. Carvalho Filho, J. Dias dos Santos · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
Neural networks and wavelet transform have been recently seen as attractive tools for developing efficient solutions for many real world problems in function approximation. Function approximation is a very important task in environments where computation has to be based on extracting information from data samples in real world processes. So, mathematical model is a very important tool to guarantee the development of the neural network area. In this article we will introduce one series of mathematical demonstrations that guarantee the wavelets properties for the PPS functions. As application, we will show the use of PPS- wavelets in pattern recognition problems of handwritten digit through function approximation techniques.