Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this work,  show the development of an adaptive algorithm based on the Ln(cosh \varepsilon) as cost function applied upon the error, called Sigmoidal Algorithm (SA). That function generates a surface which yields fast convergence along with lor misadjustment. It is similar to the family of algorithms proposed by Walach and Widrow [1]. The later ones re shown to behave poorer than the LMS algorithm [2], when the noise was Gaussian.  study the SA algorithm convergence behavior and find equations for the misadjustment and the learning time. Results shod that the SA had a better performance than the LMS when the noise had a Gaussian distribution.
['Ewaldo Santana', 'Jose C. Principe', 'Allan Kardec Barros', 'Raimundo C. S. Freire']
I am writing a research paper on a idea An Adaptive Algorithm Based On The Sigmoidal Function
[{"from": "human", "value": "I am writing a research paper on a idea An Adaptive Algorithm Based On The Sigmoidal Function"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this work,  show the development of an adaptive algorithm based on the Ln(cosh \\varepsilon) as cost function applied upon the error, called Sigmoidal Algorithm (SA). That function generates a surface which yields fast convergence along with lor misadjustment. It is similar to the family of algorithms proposed by Walach and Widrow [1]. The later ones re shown to behave poorer than the LMS algorithm [2], when the noise was Gaussian.  study the SA algorithm convergence behavior and find equations for the misadjustment and the learning time. Results shod that the SA had a better performance than the LMS when the noise had a Gaussian distribution."}]