摘要
The paper makes a description of the fuzzy filter properties considering its operational principles. A digital filter interacts with a reference model signal into real process in order to get the best corresponding answer, having the minimum error at the filter output using the mean square criterion. Adding into this filter structure a fuzzy mechanism, to obtain an intelligent filtering because adaptively select and emit a decision answer according with the external reference signal changes, in order to actualize the best correct new conditions updating a process dynamically. The interpretation of the input signal level describes the operation of the reference model, to update the filter weights giving the answers approximation in accordance with the reference signal in natural form. Finally the paper shows the simulations results of the fuzzy filter into the Kalman structure using the Matlab? tool.
The paper makes a description of the fuzzy filter properties considering its operational principles. A digital filter interacts with a reference model signal into real process in order to get the best corresponding answer, having the minimum error at the filter output using the mean square criterion. Adding into this filter structure a fuzzy mechanism, to obtain an intelligent filtering because adaptively select and emit a decision answer according with the external reference signal changes, in order to actualize the best correct new conditions updating a process dynamically. The interpretation of the input signal level describes the operation of the reference model, to update the filter weights giving the answers approximation in accordance with the reference signal in natural form. Finally the paper shows the simulations results of the fuzzy filter into the Kalman structure using the Matlab? tool.
