非线性：非线性关系是自然界的普遍特性。大脑的智慧就是一种非线性现象。人

Non-linearity: Non-linear relationship is a universal characteristic of nature. The wisdom of the brain is a nonlinear phenomenon. Artificial neurons are in two different states of activation or inhibition. This behavior is mathematically expressed as a nonlinear relationship. The network composed of neuron with threshold has better performance and can improve fault tolerance and storage capacity. <br>(2) Non-limitation: A neural network is usually composed of multiple neurons connected extensively. The overall behavior of a system not only depends on the characteristics of a single neuron, but may be mainly determined by the interaction and interconnection between the units. Simulate the non-limitation of the brain through a large number of connections between units. Associative memory is a typical example of non-limitation. <br>(3) Unsteady: Artificial neural network has the ability of self-adaptation, self-organization and self-learning. Not only can the information processed by the neural network have various changes, but while processing the information, the nonlinear dynamic system itself is also constantly changing. Often use an iterative process to describe the evolution of a dynamical system

Non-linearity: Nonlinear relationships are a common characteristic of nature. The wisdom of the brain is a nonlinear phenomenon. Artificial neurons are in two different states of activation or inhibition, which is mathematically characterized as a nonlinear relationship. A network with thresholds of nerve stoushes has better performance and can improve fault tolerance and storage capacity.<br>(2) Non-limitation: A neural network is usually made up of multiple neurons. The overall behavior of a system depends not only on the characteristics of a single neuron, but also by the interaction and connection of the cells. The non-limitations of the brain are simulated through a large number of connections between cells. Lenovo memory is a typical example of non-limitation.<br>(3) Non-normality: artificial neural networks have adaptive, self-organizing and self-learning abilities. Neural networks not only process information can have various changes, but also processing information at the same time, the nonlinear dynamic system itself is constantly changing. Iterative processes are often used to describe the evolution of the power system.

Nonlinearity: nonlinear relationship is a universal characteristic of nature. Brain intelligence is a nonlinear phenomenon. Artificial neurons are in two different states of activation or inhibition, which is a nonlinear relationship in mathematics. The neural network with threshold has better performance and can improve fault tolerance and storage capacity.<br>(2) Non limitation: a neural network is usually composed of multiple neurons. The overall behavior of a system depends not only on the characteristics of individual neurons, but also on the interaction and connection between units. Through a large number of connections between units, the brain's non limitation is simulated. Associative memory is a typical example of non limitation.<br>(3) Unsteadiness: artificial neural network has the ability of self adaptation, self-organization and self-learning. Neural network not only can deal with various changes in information, but also in the processing of information, the nonlinear dynamic system itself is constantly changing. Iterative process is often used to describe the evolution process of dynamic system<br>