In order to study the overall function of the brain, an understanding of substructure and the interactions between parts of the brain is necessary. Feedforward networks illustrate one way to build a network out of parts. A second model of interacting subnetworks is a subdivided attractor network...
neural network n 1. (Physiology) an interconnected system of neurons, as in the brain or other parts of the nervous system 2. (Computer Science) Also called: neural net an analogous network of electronic components, esp one in a computer designed to mimic the operation of the human brain...
Using the brain-inspired Neural circuit Evolution strategy (NeuEvo) with rich neural circuit types, the evolved spiking neural network greatly enhances capability on perception and reinforcement learning tasks. 本文通过结合前馈和反馈连接以及兴奋性和抑制性神经元,提供了一个更符合生物学可行性的进化空间。
and forecast future events. A neural network breaks down the input into layers of abstraction. It can be trained using many examples to recognize patterns in speech or images just as the human brain does. The neural network behavior is defined by the way its individual elements are connected ...
neural networkorneural computing,computerarchitecture modeled upon the humanbrain's interconnected system of neurons. Neural networks imitate the brain's ability to sort out patterns and learn from trial and error, discerning and extracting the relationships that underlie the data with which it is pres...
Recent hierarchical convolutional neural networks (CNNs) have achieved human-like object categorization performance1,2,3,4. It has additionally been shown that representations formed in lower and higher layers of the network track those of the human lower and higher visual processing regions, respectiv...
Of course, this argument is far from rigorous, and shouldn't be taken too seriously. Still, it can sometimes be a useful starting point. and we train for 3030 epochs. The interface to network2.py is slightly different than network.py, but it should still be clear what is going on. ...
neural network noun : a computer architecture in which a number of processors are interconnected in a manner suggestive of the connections between neurons in a human brain and which is able to learn by a process of trial and error called also neural net examples of neural network in a ...
Brain modeling by tensor network theory and computer simulation. The cerebellum: distributed processor for predictive coordination. Neuroscience 4, 323–348 (1979). CAS PubMed Google Scholar Rolls, E. T. & Treves, A. Neural Networks and Brain Function (Oxford Univ. Press, 1998). Google ...
Neural networks, in the world of finance, assist in the development of such processes as time-series forecasting,algorithmic trading, securities classification, credit risk modeling, and constructing proprietary indicators and pricederivatives. A neural network works similarly to the human brain’s neural...