Date of Award
Master of Science in Engineering
Electrical and Computer Engineering
Dr. Janos L. Grantner
Dr. Massood Zandi Atashbar
Dr. Bradley J. Bazuin
Fuzzy, automata, reconfiguration, zynq FPGA board, embedded
Masters Thesis-Open Access
As embedded systems have become more complex and designers are required to develop new products faster while using fewer chips. FPGAs are a good choice because they offer flexibility to design on-chip devices as well as the embedded systems that are reprogrammable and reconfigurable. Today's tougher cost, higher performance, and lower power consumption requirements demand even more efficient design strategies. Dynamic partial reconfiguration (PR) is a good approach to meet these requirements because it extends the inherent flexibility of the FPGA by allowing partial regions of the FPGA to be dynamically reconfigured with new functionality while other applications are still running in the remainder of the device. Partial reconfiguration offers significant advantages compared with the traditional full reconfiguration. Designers can keep the hardware resource utilization low because they can dynamically load more logic circuits into single device in a sequential fashion. Moreover, designers can improve the productivity and scalability of their systems because they need only modify, or revise those functions that are required by a particular application .
In the last few decades, computational intelligence has been applied to transform human behavior and experience into mathematical representations that can be interpreted by computer programs. The development of intelligent control systems and intelligent decision support systems are part of this trend. In this Thesis, VHDL and Zynq-7000 FPGA board have been used to design all hardware modules, and a hardware accelerator of fuzzy automata – based decision support system in the context of eye-hand coordination testing for handicapped children was defined and developed.
Nguyen, "Design of Hardware Accelerator for Fuzzy Automata Using Dynamic Partial Reconfiguration" (2014). Master's Theses. 477.