外文翻譯---人工神經(jīng)網(wǎng)絡(luò)-wenkub
2023-05-19 10:52:37 本頁面
【正文】 e nonlinear relationship is the nature of the nonlinear mon characteristics. The wisdom of the brain is a kind of nonlinear phenomena. Artificial neurons in the activation or inhibit the two different state, this kind of behavior in mathematics performance for a nonlinear relationship. Has the threshold of neurons in the work formed by the has better properties, can improve the fault tolerance and storage capacity. (2) the limitations a neural work by DuoGe neurons widely usually connected to. A system of the overall behavior depends not only on the characteristics of single neurons, and may mainly by the unit the interaction between the, connected to the. Through a large number of connection between units simulation of the brain limitations. Associative memory is a typical example of limitations. (3) very qualitative artificial neural work is adaptive, selforganizing, learning ability. Neural work not only handling information can have all sorts of change, and in the treatment of the information at the same time, the nonlinear dynamic system itself is changing. Often by iterative process description of the power system evolution. (4) the convexity a system evolution direction, in certain conditions will depend on a particular state function. For example energy function, it is corresponding to the extreme value of the system stable state. The convexity refers to the function extreme value, it has DuoGe DuoGe system has a stable equilibrium state, this will cause the system to the diversity of evolution. Artificial neural work, the unit can mean different neurons process of the object, such as characteristics, letters, concept, or some meaningful abstract model. The type of work processing unit is divided into three categories: input unit, output unit and hidden units. Input unit accept outside the world of signal and data。s real world puting (springboks claiming) project, artificial intelligence research into an important ponent. Network model Artificial neural work model of the main consideration work connection topological structure, the characteristics, the learning rule neurons. At present, nearly 40 kinds of neural work model, with back propagation work, sensor, selforganizing mapping, the Hopfield puter, wave boltzmann machine, adapt to the ear resonance theory. According to the topology of the connection, the neural work model can be divided into: (1) prior to the work before each neuron accept input and output level to the next level, the work without feedback, can use a loop to no graph. This work realization from the input space to the output signal of the space transformation, it information processing power es from simple nonlinear function of DuoCi pound. The work structure is simple, easy to realize. Against the work is a kind of typical prior to the work. (2) the feedback work between neurons in the work has feedback, can use a no to plete the graph. This neural work information processing is state of transformations, can use the dynamics system theory processing. The stability of the system with associative memory function has close relationship. The Hopfield puter, wave ear boltzmann machine all belong to this type. Learning type Neural work learning is an important content, it is through the adaptability of the realization of learning. According to the change of environment, adjust to weights, improve the behavior of the system. The proposed by the Hebb Hebb learning rules for neural work learning algorithm to lay the foundation. Hebb rules say that learning process finally happened between neurons in the synapse, the contact strength synapses parts with before and after the activity and synaptic neuron changes. Based on this, people put forward various learning rules and algorithm, in order to adapt to the needs of different work model. Effective learning algorithm, and makes the god The work can through the weights between adjustment, the structure of the objective world, said the formation of inner characteristics of information processing method, information storage and processing reflected in the work connection. According to the learning environment is different, the study method of the neural work can be divided into learning supervision and unsupervised learning. In the supervision and study, will the
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