water quality assessment provides a scientific basis for water resources development and management. this case study proposes a factor analysis- hopfield neural network model (fhnn) based on factor analysis method and hopfield neural network method. the results showed that the factor analysis (fa) technique was introduced to identify important water quality parameters. results revealed that bio...

Hopfield Neural Networks have been used as universal identifiers of non-linear systems, because of their inherent dynamic properties. However the design decision of the number of neurons in the Hopfield network is not easy to make, in order for the network model to have the necessary complexity, extra neurons are required. This poses a problem since the role of the states that these neurons rep...

The deterministic limit of a Hopfield-type mutation-selection model in the sequence space approach is investigated. Genotypes are identified with two-letter sequences. Mutation is modelled as a Markov process, fitness functions are of Hopfield type, where the fitness of a sequence is determined by the Hamming distances to a number of predefined patterns. Using a maximum principle for the popula...

The Hopfield network (Hopfield, 1982,1984) provides a simple model of an associative memory in a neuronal structure. This model, however, is based on highly artificial assumptions, especially the use of formal-two state neu-rons (Hopfield, 1982) or graded-response neurons (Hopfield, 1984). \Vhat happens if we replace the formal neurons by 'real' biological neurons? \Ve address this question in ...