Description: Neural signal processing refers to the analysis and interpretation of electrical signals generated by neurons in the nervous system. Using artificial intelligence (AI) techniques, this field seeks to unravel patterns and correlations in neural data, allowing for a deeper understanding of brain activity. Neural signals are complex and can vary in frequency, amplitude, and duration, making their analysis require advanced tools. AI, especially through machine learning algorithms and deep neural networks, has become a crucial ally in this process, facilitating the identification of relevant features and the prediction of behaviors. This approach not only improves accuracy in interpreting neural data but also enables the creation of models that can simulate brain activity under various conditions. The combination of neural signal processing and AI techniques has the potential to revolutionize fields such as neuroscience, medicine, and robotics, providing new insights into brain function and its interaction with artificial systems.
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