The computer simulation results showed that the proposed algorithm was superior to original particle swarm optimization algorithms and was effective in separating nonlinear blind sources.
计算机仿真结果表明该算法的收敛性能优于粒子群优化算法，并且在非线性盲信号分离中是有效的。
To establish mathematical model, various nonlinear factors are seriously considered, which can constrict the error between result of computer simulation after theoretical analysis and result of test.
在建立数学模型时，充分考虑了各非线性因素，缩小了理论分析、计算机仿真结果与试验结果之间的误差。
Computer simulation demonstrates that nonlinear local optimization methods are effective for EEG inverse solution if the source number is one or two and the initial iterative values are reasonable.
仿真结果表明，在处理一个或两个源场的情况下，如果迭代初值选择合理，非线性局域优化方法可以有效地解决脑电逆问题。
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