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Full-Text Articles in Engineering
Learning Nonlinear Functions With Mlps And Srns, R. Cleaver, Ganesh K. Venayagamoorthy
Learning Nonlinear Functions With Mlps And Srns, R. Cleaver, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, nonlinear functions generated by randomly initialized multilayer perceptrons (MLPs) and simultaneous recurrent neural networks (SRNs) are learned by MLPs and SRNs. Training SRNs is a challenging task and a new learning algorithm - DEPSO is introduced. DEPSO is a standard particle swarm optimization (PSO) algorithm with the addition of a differential evolution step to aid in swarm convergence. The results from DEPSO are compared with the standard backpropagation (BP) and PSO algorithms. It is further verified that functions generated by SRNs are harder to learn than those generated by MLPs but DEPSO provides better learning capabilities for …
Learning Functions Generated By Randomly Initialized Mlps And Srns, R. Cleaver, Ganesh K. Venayagamoorthy
Learning Functions Generated By Randomly Initialized Mlps And Srns, R. Cleaver, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, nonlinear functions generated by randomly initialized multilayer perceptrons (MLPs) and simultaneous recurrent neural networks (SRNs) and two benchmark functions are learned by MLPs and SRNs. Training SRNs is a challenging task and a new learning algorithm - PSO-QI is introduced. PSO-QI is a standard particle swarm optimization (PSO) algorithm with the addition of a quantum step utilizing the probability density property of a quantum particle. The results from PSO-QI are compared with the standard backpropagation (BP) and PSO algorithms. It is further verified that functions generated by SRNs are harder to learn than those generated by MLPs …