Bigradient neural network-based quantum particle swarm optimization for blind source separation

<p><span id="docs-internal-guid-df1e3816-7fff-2396-860a-693df6c8ad2e"><span>An independent component analysis (ICA) is one of the solutions a blind source separation problem. ICA statistical approach that depends on properties mixed signals. The purpose method to demix signals (observation signals) and rcovering those abbreviation problem needs for optimizing by using optimization approaches as swarm intelligent, neural neworks, genetic algorithms. This paper presents hybrid optimize quantum particle (QPSO) Bigradient network applies separate recover sources results an implement this work prove gave good comparing with other methods such QPSO method, based several evaluation measures signal-to-noise ratio, signal-to-distortion absolute value correlation coefficient, computation time.</span></span></p>