近年来，高阶神经网络（HONNs）在控制信号生成、模式识别、非线性识别、分类以及控制和识别场景的预测等方面得到了广泛的应用。由于HONNs已被证明比传统神经网络更快、更准确、更易于解释，因此它们的应用是无限的。
用于控制和识别的应用人工高阶神经网络探索了专门用于智能技术应用的高阶神经网络的集成方式。强调新兴的研究、实践和现实世界的实施，这本及时的参考出版物是研究人员、IT专业人员和计算机科学与工程研究生的重要参考资料来源。
Applied Artificial Higher Order Neural Networks for Control and Recognition
In recent years, Higher Order Neural Networks (HONNs) have been widely adopted by researchers for applications in control signal generating, pattern recognition, nonlinear recognition, classification, and predition of control and recognition scenarios. Due to the fact that HONNs have been proven to be faster, more accurate, and easier to explain than traditional neural networks, their applications are limitless.
Applied Artificial Higher Order Neural Networks for Control and Recognition explores the ways in which higher order neural networks are being integrated specifically for intelligent technology applications. Emphasizing emerging research, practice, and real-world implementation, this timely reference publication is an essential reference source for researchers, IT professionals, and graduate-level computer science and engineering students.
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