Basic Concepts of Neural Networks and Fuzzy Logic

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“…Whereas the axon is the output part of a neuron, the dendrites are input elements, which receive synaptic signals from other neurons. The transmission of signals is achieved by diffusion of chemicals called neurotransmitters [2].…”

“…ANNs are inspired and based on the function of BNNs trying to simulate the learning process of the human brain [2,3]. The term "artificial" means that ANNs are implemented in computer programs being able to handle the large number of necessary calculations during the learning process (neural computing, [31]).…”

“…The applications of ANNs include analysis, classification and recognition of data, pattern recognition, control, associative memory, image processing and compression, forecasting applications, weather and stock market prediction, security and loan applications, etc. [2,3,33].…”

“…The ANNs, having the ability to learn and to process the information rapidly, concentrate on the "hardware" of the human brain, whereas fuzzy systems concentrate on the "software" emulating human reasoning. Figure 5 represents graphically the relationships among ANNs, FL and probabilistic reasoning within the wider class of SC [2]. The intersections in Figure 5 include probabilistic approaches to ANNs and FL systems, BR and neuro-fuzzy systems, which are hybrid systems using a learning algorithm from an ANN to determine their fuzzy parameters.…”

“…The theory and techniques of Soft Computing (SC) were introduced during the 1980"s by the pioneer of FL Lofti Zadeh, who defined it as "an emerging approach to computing, which parallels the remarkable ability of the human mind to reason and learn in an environment of uncertainty and imprecision" [1]. In contrast to the conventional methods of hard computing, which are based on symbolic logical reasoning and numerical modelling, the methods of SC deal with approximate reasoning and processes that give solutions to complex real-life problems, which are too difficult to be modelled mathematically [1][2][3][4]. Its implementations in intelligent control, decision making support, nonlinear programming, etc., have made SC popular for people of a wide variety of disciplines and scientific backgrounds, like engineers, computer scientists and mathematicians, other natural and positive scientists, etc.…”