Title :
A supervised neural constant bit rate video controller for MPEG2 encoders
Author :
De Castro, Fernando C C ; De Castro, Maria C F ; Arantes, Dalton S.
Author_Institution :
Dept. de Comunicacoes, Univ. Estadual de Campinas, Sao Paulo, Brazil
Abstract :
A supervised training algorithm is used in a radial basis function neural network in order to improve the performance of a recently introduced nonlinear predictive rate controller for MPEG2 encoders. The algorithm, which is based on the stochastic gradient method, is used for updating the radial basis centers. By means of extensive computer simulation with standard video sequences, practical design parameters are presented for buffer control in constant bit rate MPEG2 video encoders
Keywords :
buffer storage; gradient methods; image sequences; learning (artificial intelligence); predictive control; radial basis function networks; stochastic processes; video coding; MPEG2 encoders; buffer control; computer simulation; constant bit rate encoders; nonlinear predictive rate controller; performance; radial basis center updating; radial basis function neural network; stochastic gradient method; supervised training algorithm; video sequences; Artificial neural networks; Bit rate; Electronic mail; Layout; Neural networks; Neurons; Radial basis function networks; Signal to noise ratio; Stochastic processes; Vectors;
Conference_Titel :
Telecommunications Symposium, 1998. ITS '98 Proceedings. SBT/IEEE International
Conference_Location :
Sao Paulo
Print_ISBN :
0-7803-5030-8
DOI :
10.1109/ITS.1998.718445
