Architectural Exploration for Energy-Efficient LMS and NLMS Adaptive Filters VLSI Design
Objective
This work proposes architectural solutions for LMS and NLMS algorithms targeting an energy-efficient VLSI design.
Abstract
The pursuit of energy-efficient integrated circuits has become paramount in the face of growing demand for power-efficient signal processing systems. This paper presents an in-depth architectural exploration focused on the design and optimization of Least Mean Square (LMS) and Normalized LMS (NLMS) adaptive filters in Very Large Scale Integration (VLSI) technology.
The study delves into various architectural choices, exploring trade-offs between power efficiency, computational complexity, and filter performance. By leveraging innovative design methodologies and algorithmic optimizations, we introduce novel architectures that significantly reduce power consumption while maintaining or enhancing adaptive filter performance.
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Block Diagram
Specifications
Specifications:
Software Requirements:
· Tool: Xilinx Vivado
· 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
Learning Outcomes
Learning Outcomes:
· Introduction to digital & analog electronics
· Understanding of VLSI Concepts
· Understanding of Adaptive Filtering Concepts
· Knowledge on Verilog
· Algorithmic understanding & Exploration
· Simulation & Verification
· Testing & Debugging skills
· Real world Applications
Related Projects
Paper Publishing
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