Neural networks can refer to two types: one is biological neural networks and the other is artificial neural networks./5 @: N/ V7 @: X5 _1 X) BBiological neural networks: Generally refer to the networks composed of neurons, cells, synapses, etc. in the biological brain, used to generate biological consciousness and help organisms think and act.Artificial Neural Networks (ANNs), also referred to as neural networks (NNs) or connection models, are mathematical models that mimic the behavioral characteristics of animal neural networks for distributed and parallel information processing. This network relies on the complexity of the system, adjusting the relationships between a large number of internal nodes to achieve information processing.Artificial neural networks: are mathematical models that process information using structures similar to the synaptic connections of brain neurons. In engineering and academia, they are often simply referred to as “neural networks” or neuro-networks.Mathematical modeling is often used in the following aspects:! Model establishment based on research of biological prototypes, to establish theoretical models of neurons and neural networks. This includes conceptual models, knowledge models, physical-chemical models, mathematical models, etc. Algorithms are constructed based on theoretical model research to create specific neural network models for computer simulation or hardware preparation, including research on network learning algorithms. This work is also known as technical model research.The algorithms used in neural networks are vector multiplication, and they widely adopt symbolic functions and various approximations. Parallelism, fault tolerance, hardware implementation, and self-learning characteristics are some of the basic advantages of neural networks, distinguishing their computational methods from traditional methods.8 ^: v” W- P’ E3 U0 JBased on the research of network models and algorithms, practical application systems can be created using artificial neural networks, such as completing certain signal processing or pattern recognition functions, constructing expert systems, creating robots, complex system control, etc.Throughout the history of the development of contemporary emerging scientific and technological fields, humanity has traveled a rugged road in conquering outer space, fundamental particles, the origin of life, and other scientific and technological domains. We will also see that the research exploring the functions of the human brain and neural networks will continue to evolve rapidly as we overcome numerous difficulties.Download the attachment to learn! Resource link: http://www.madio.net/thread-363694-1-7.html
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