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- Neural Field Description: The neural field theory is a mathematical framework that seeks to understand the dynamics of neural networks by representing their(...) Read more
- Neural Mapping Description: Neural mapping is the process by which input data is associated with output data in a neural network. This process is fundamental(...) Read more
- Neural Fusion Description: Neural fusion refers to the integration of multiple neural networks or their outputs to enhance the accuracy and robustness of(...) Read more
- Neural Synthesis Description: Neural synthesis is the process by which new data is generated based on patterns learned in a neural network. This process involves(...) Read more
- Neural Interface Description: A neural interface is a system that allows interaction between neural networks and other systems, facilitating communication and(...) Read more
- Neural Convergence Description: Neural convergence refers to the process in which multiple neural networks or pathways lead to a common output. This concept is(...) Read more
- Neural Feedback Loop Description: The neural feedback loop is a system where the output of a neural network is fed back into the input, creating a continuous cycle(...) Read more
- Neurons Description: Neurons are the basic building blocks of neural networks that process input and produce output. Each neuron simulates the behavior(...) Read more
- Neural Information Processing Description: Neural information processing refers to how neural networks mimic the functioning of the human brain to process data and learn from(...) Read more
- Neural Layer Description: A neural layer is a collection of neurons that work together to process input data. In the context of recurrent neural networks(...) Read more
- Neural Training Description: Neural training is the process of adjusting the weights of a neural network to minimize the error in its predictions. In the(...) Read more
- Neural Adaptation Description: Neural adaptation refers to the ability of a neural network, especially in the context of recurrent neural networks (RNNs), to(...) Read more
- Neural Generalization Description: Neuronal generalization refers to the ability of a neural network to perform well on unseen data, that is, data that was not part(...) Read more
- Neural Complexity Description: Neuronal complexity refers to the level of sophistication in the architecture and functioning of a neural network. This concept(...) Read more
- Neural Constraints Description: Neural constraints are limitations imposed on the architecture or functioning of a neural network, which can influence its ability(...) Read more
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