The primary goal seems to be creating a resource-efficient and high-accuracy digital implementation of the Hodgkin-Huxley neuron model on FPGA platforms 4. This involves addressing several challenges related to the complexity of the Hodgkin-Huxley model and the limitations of FPGA resources.
A new and efficient Hodgkin–Huxley (HH) neuron has been implemented on field-programmable gate array (FPGA). Multiplication, division, and exponential terms were implemented using the COordinate Rotation DIgital Computer (CORDIC) algorithm with carefully selected iteration numbers for each operation to greatly reduce the hardware resource requirements while simultaneously maintaining system throughput and a maximum clock frequency of over 275 MHz. The proposed design achieves higher modeling accuracy than previously proposed designs and an accuracy-resource trade-off that represents dramatic improvements. Additionally, all the neuron’s physiological parameters are variable as inputs to the proposed design postimplementation for a high degree of freedom in neuroscientific simulations. The implemented neuron is presented with results, and the behavior of the implemented system is evaluated to verify its close behavioral matching to the target neuron model.
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Software Requirements:
· Xilinx Vivado Tool
· HDL: Verilog
Hardware Requirements:
· Microsoft® Windows XP
· Intel® Pentium® 4 processor or Pentium 4 equivalent with SSE support
· 512 MB RAM
· 100 MB of available disk space
o Data Flow modelling
o Structural modelling
o Behavioural modelling
o Mixed level modelling
· Xilinx Vivado for design and simulation
· Generation of Netlist
· Solution providing for real time problems
· Project Development Skills:
o Problem Analysis Skills
o Problem Solving Skills
o Logical Skills
o Designing Skills
o Testing Skills
o Debugging Skills
o Presentation Skills
o Thesis Writing Skills