Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  examines a method to apply to channel equalization problem by model selection. The selection process is based on finding a subset model to approximate the response of the full two ighted neural network model for the current input vector, and not for the entire input space. When the channel equalization problem is non-stationary, the requirement to update all the kernel ighs locations is removed, and its complexity is reduced. Using computer simulations,  show that the number of kernel ights can be greatly reduced without compromising classification performance.
['Wenming Cao', 'Shoujue Wang']
I am writing a research paper on a idea Study of adaptive equalizers based on two weighted neural networks
[{"from": "human", "value": "I am writing a research paper on a idea Study of adaptive equalizers based on two weighted neural networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  examines a method to apply to channel equalization problem by model selection. The selection process is based on finding a subset model to approximate the response of the full two ighted neural network model for the current input vector, and not for the entire input space. When the channel equalization problem is non-stationary, the requirement to update all the kernel ighs locations is removed, and its complexity is reduced. Using computer simulations,  show that the number of kernel ights can be greatly reduced without compromising classification performance."}]