In this work, alternative design and implementation techniques for feature extraction applications are proposed. The proposed techniques amount to decomposing the overall feature extraction problem into a global linear system followed by a local nonlinear system. Different output representations for representation of input features are also allowed and used in these techniques. These different output representations bring cui additional degree of freedom to the feature extraction problems. The systems provide multi-outputs consisting of different features of the input signal or image. Efficient implementation of the linear part of the .system is obtained by using fractional Fourier filtering circuits. Expressions for the proposed techniques are derived and several illustrative examples cxre given in which efficient implementations for feature extraction applications are obtained.