Research On Fuzzy Associative Memory Networks And Fuzzy Image Processing

The fuzzy theory and fuzzy technique are the current focus of academia at present. Around the fuzzy neural networks and fuzzy image processing, Fuzzy Associative Memory (FAM) neural networks and the removal of noise in image are studied, some new algorithms are proposed and some new implementation algorithms are proposed in this dissertation. The main works are listed as follows:1) Because the max-min composition fuzzy Hebb Fuzzy Associative Memories (FAM) networks model proposed by Bart Kosko can't ensure multiple fuzzy pattern pairs to be encoded in a FAM associated weight matrix, a new neural networks learning algorithms for multiple-pattem pairs connection weight matrix of FAM and its relevant theoretical results and strict mathematics proofs are presented. At the same time, its effectiveness is testified by simulations. The algorithm is used to solve the problem of storage for multiple fuzzy pattern pairs successfully. Multiple fuzzy pattern pairs can be encoded to store in associated weight matrixes of FAM as few as possible by the algorithm, so it can cut down storage space and improves its storage capacity greatly, moreover this algorithm can easily be implemented. For the bi-directional FAM, a kind of neural network learning algorithms for associated weight matrix is presented and its fault-tolerances is discussed too.2) Generalize the algorithm of max-min composition FAM aforementioned into max-T norm operations FAM. Neural networks learning algorithm for associated weight matrix of fuzzy associative memory which is based on a class of T -norm operations and its theoretic results and strict mathematics proofs are presented. If the interior operator of FAM networks is different, the different purposes and effects of FAM system can be obtained, so the algorithm extends the application of FAM greatly.3) Based on literature [122], a new filter—Fuzzy Detection Weighted Mean (FDWM) filter is presented in this dissertation. According to the histogram of corrupted image and its statistic characteristic, first we construct the fuzzy membership functions...