Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a method for evaluating functions in hardware based on polynomial approximation with non-uniform segments. The novel use of non-uniform segments enables us to approximate non-linear regions of a function particularly ll. The appropriate segment address for a given function can be rapidly calculated in run time by a simple combinational circuit. Scaling factors are used to deal with large polynomial coefficients and to trade precision with range. Our function evaluator is based on first-order polynomials, and is suitable for applications requiring high performance with small area, at the expense of accuracy. The proposed method is illustrated using two functions, -ln(x) and cos(2πx), which have been used in Gaussian noise generation.
['Dong-U Lee', 'Wayne Luk', 'John Villaseno', 'Peter Y. K. Cheung']
I am writing a research paper on a idea Non-uniform segmentation for hardware function evaluation
[{"from": "human", "value": "I am writing a research paper on a idea Non-uniform segmentation for hardware function evaluation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a method for evaluating functions in hardware based on polynomial approximation with non-uniform segments. The novel use of non-uniform segments enables us to approximate non-linear regions of a function particularly ll. The appropriate segment address for a given function can be rapidly calculated in run time by a simple combinational circuit. Scaling factors are used to deal with large polynomial coefficients and to trade precision with range. Our function evaluator is based on first-order polynomials, and is suitable for applications requiring high performance with small area, at the expense of accuracy. The proposed method is illustrated using two functions, -ln(x) and cos(2\u03c0x), which have been used in Gaussian noise generation."}]