ABSTRACT
The real-time rendering process is inherently non-linear. This can be understood from the fact that computer systems on which software runs are constructed using electronic components that exhibit non-linear material properties. This chapter describes an approach by which this non-linear characteristic can be captured sufficiently with appropriate system models using advanced techniques in soft computing. It introduces the application of artificial neural networks (ANNs) to model the non-linearity in the real-time rendering process. Dynamic neural networks use memory and recurrent feedback connections to capture temporal patterns in data. The choice of using ANNs to model a computing process such as real-time rendering may be explained easily. The dynamics of an ANN arising from delay units within its structure provides an inferred correspondence with the architecture of current computing hardware. A delay usually occurs in embedded circuits when data are transferred between the processor and memory units.
