Considering the disadvantage of the algorithms based on statistics
a novel algorithm based on Complex Hopfield Neural Network with Real-Imaginary-type Soft-Multistate-activation-function (CHNN_RISM) is proposed to detect QAM signals blindly.A multi-valued continuous activation function is constructed in both of the real part and imaginary part of CHNN_RISM.A new energy function for CHON_RISM is constructed in this paper and the stabilities with asynchronous and synchronous operating mode are also analyzed separately.While the weighted matrix of CHNN_RISM is constructed by the complementary projection operator of received signals
the problem of quadratic optimization with integer constraints can successfully solved with the CHNN_RISM
and the QAM signals are blindly detected.Simulation results show that the algorithm reaches the real equilibrium points with shorter received signals and appropriate for channel with common zeros.