Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Existing systolic architectures for the LMS algorithm with delayed coefficient adaptation have large adaptation delay and hence degraded convergence behaviour.  presents a systolic architecture with minimal adaptation delay and input/output latency, thereby improving the convergence behaviour to near that of the original LMS algorithm. The architecture is synthesized by using a number of function preserving transformations on the signal flow graph representation of the delayed LMS algorithm. With the use of carry-save arithmetic, the systolic folded pipelined architecture can support very high sampling rates, limited only by the delay of a full adder.
['S. Ramanathan', 'V. Visvanathan']
I am writing a research paper on a idea A systolic architecture for LMS adaptive filtering with minimal adaptation delay
[{"from": "human", "value": "I am writing a research paper on a idea A systolic architecture for LMS adaptive filtering with minimal adaptation delay"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Existing systolic architectures for the LMS algorithm with delayed coefficient adaptation have large adaptation delay and hence degraded convergence behaviour.  presents a systolic architecture with minimal adaptation delay and input/output latency, thereby improving the convergence behaviour to near that of the original LMS algorithm. The architecture is synthesized by using a number of function preserving transformations on the signal flow graph representation of the delayed LMS algorithm. With the use of carry-save arithmetic, the systolic folded pipelined architecture can support very high sampling rates, limited only by the delay of a full adder."}]