mhist.txt

The neuro-fuzzy software for identification and data analysis has been implemented in the MATLAB lan

				Consequents optimization. SSE=48.7616
Premise optimization: 0/3 epochs, mu = 0.001, SSE= 48.7616.
Premise optimization: 1/3 epochs, mu = 0.0001, SSE= 37.1316.
Premise optimization: 2/3 epochs, mu = 0.001, SSE= 33.2741.
Premise optimization: 3/3 epochs, mu = 0.1, SSE= 33.2698.
				Consequents optimization. SSE=10.1379
Premise optimization: 0/3 epochs, mu = 0.001, SSE= 10.1379.
Premise optimization: 1/3 epochs, mu = 0.0001, SSE= 5.40735.
				Consequents optimization. SSE=4.27967
Premise optimization: 0/3 epochs, mu = 0.001, SSE= 4.27967.
				Consequents optimization. SSE=4.27967
Premise optimization: 0/3 epochs, mu = 0.001, SSE= 4.27967.
				Consequents optimization. SSE=4.27967
Premise optimization: 0/3 epochs, mu = 0.001, SSE= 4.27967.