Research Article

Design of Adaptive Filter Using Jordan/Elman Neural Network in a Typical EMG Signal Noise Removal

Table 2

For hidden layers  = 3, input PE  = 1, output PE  = 1, transfer function  = TanhAxon, learning rule  = momentum, maximum epochs  = 1000, and threshold MSE  = 0.01.

Serial no.Type of ANNHidden layer variation H1 H2 H3Correlation coefficient MSE ( s)
TrainingCross validationTesting

01Jordan/Elman network08,04,020.781 188 7250.009 985 3150.020 162 0120.014 843 2029.78266.4

02Jordan/Elman network08,04,020.805 945 0710.009 983 6310.021 040 7790.015 119 3729.78266.5

03Jordan/Elman network08,05,040.753 974 7790.009 980 0050.019 238 1820.014 509 8816.521723.8

04Jordan/lman network08,05,040.793 330 8320.009 983 9420.02 0150 5380.014 729 3646.521718.8