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METHODS AND SYSTEMS FOR BANKED RADIAL BASIS FUNCTION NEURAL NETWORK BASED NON-LINEAR INTERFERENCE MANAGEMENT FOR MULTI-TECHNOLOGY COMMUNICATION DEVICES
METHODS AND SYSTEMS FOR BANKED RADIAL BASIS FUNCTION NEURAL NETWORK BASED NON-LINEAR INTERFERENCE MANAGEMENT FOR MULTI-TECHNOLOGY COMMUNICATION DEVICES
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机译:多技术通信设备的基于存储径向基函数神经网络的非线性干扰管理方法和系统
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摘要
The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a radial basis function neural network with Hammerstein structure by executing a radial basis function on aggressor signals at a hidden layer of the radial basis function neural network with Hammerstein structure to obtain hidden layer outputs, augmenting aggressor signal(s) by weight factors and, executing a linear combination of the augmented output, at an intermediate layer to produce a combined hidden layer outputs. At an output layer, a linear filter function may be executed on the hidden layer outputs to produce an estimated nonlinear interference used to cancel the nonlinear interference of a victim signal.
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