Systolic VLSI array for multi-variable fuzzy control systems
Cybernetics and Systems
Digital design (2nd ed.)
VLSI fuzzy chip and inference accelerator board systems
Fuzzy logic for the management of uncertainty
Fuzzy logic, neural networks, and soft computing
Communications of the ACM
Essentials of fuzzy modeling and control
Essentials of fuzzy modeling and control
Special-purpose architectures for fuzzy logic controllers
Microprocessing and Microprogramming
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Hierarchical fuzzy modelling for monitoring depth of anaesthesia
Fuzzy Sets and Systems - Special issue on neuro-fuzzy techniques and applications
Algorithms for VLSI Physical Design Automation
Algorithms for VLSI Physical Design Automation
Implementing Fuzzy Rule-Based Systems on Silicon Chips
IEEE Expert: Intelligent Systems and Their Applications
Automated memory-aware application distribution for Multi-processor System-on-Chips
Journal of Systems Architecture: the EUROMICRO Journal
Microprocessors & Microsystems
Multiplierless implementation of 2-D FIR filters
Integration, the VLSI Journal
Transductive reliability estimation for medical diagnosis
Artificial Intelligence in Medicine
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The paper presents the ASIC design of a digital fuzzy logic circuit for medical diagnostic applications. The system on chip under consideration uses fuzzifier, memory and defuzzifier for fuzzifying the patient data, storing the membership function values and defuzzifying the membership function values to get the output decision. The proposed circuit uses triangular trapezoidal membership functions for fuzzification patients' data. For minimizing the transistor count, the proposed circuit uses 3T XOR gates and 8T adders for its design. The entire work has been carried out using TSMC 0.35 µm CMOS process. Post layout TSPICE simulation of the whole circuit indicates a delay of 31.27 ns and the average power dissipation of the system on chip is 123.49 mW which indicates a less delay and less power dissipation than the comparable embedded systems reported earlier.