VLSI Synthesis of Heterogeneous and SIRM Fuzzy System for Classification of Diabetic Epilepsy Risk Levels

Abstract

The objective of this paper is to design, simulate, and synthesis a simple, suitable and reliable VLSI fuzzy processor for classification of diabetic epilepsy risk levels. The performance of three different fuzzy techniques are analyzed and compared. While designing the fuzzy processor the cerebral blood flow (CBF), EEG signal features and aggregation operators are taken as parameters. The classification of risk level is based on clinical data and observation. Three different fuzzy techniques with minimum rules such as a two input heterogeneous fuzzy technique, single input rule models (SIRM) are analyzed. The parallel architecture is incorporated in this design with independent functional units. These functional units process the data simultaneously by which the processing speed is enhanced. The SIRM fuzzy system with Bell input - Bell output, and Bell input-Triangle output are simulated and synthesized for various values of Cerebral Blood Flow using VHDL. The simulated and synthesized field programmable gated array (FPGA) fuzzy processor closely follows the mat lab version.