Even since the introduction of backpropagation in 1986,

neural networks have gained considerable attention from

researchers for more than two decades now. A variety of

neural network models have been designed and applied

successfully to solve real-world problems in various

domains. Neural networks have also been widely synergized

with other machine learning and complementary

techniques to achieve improvements in robustness, adaptivity,

and applicability. In this special issue, a total of

seven articles, based on extended papers the 12th

International Conference on Knowledge-Based and Intelligent

Information & Engineering Systems (KES2008) as

well as other submissions, are presented. These

papers form a small sample of research in demonstrating

the usefulness of intelligent information processing techniques

in the design and application of neural networks. A

summary of each paper is as follows.

-Even since the introduction of backpropagation in 1986,

neural networks have gained considerable attention from

researchers for more than two decades now. A variety of

neural network models have been designed and applied

successfully to solve real-world problems in various

domains. Neural networks have also been widely synergized

with other machine learning and complementary

techniques to achieve improvements in robustness, adaptivity,

and applicability. In this special issue, a total of

seven articles, based on extended papers　the 12th

International Conference on Knowledge-Based and Intelligent

Information & Engineering Systems (KES2008) as

well as　other submissions, are presented. These

papers form a small sample of research in demonstrating

the usefulness of intelligent information processing techniques

in the design and application of neural networks. A

summary of each paper is as follows.