Invention Application
US20160071007A1 Methods and Systems for Radial Basis Function Neural Network With Hammerstein Structure Based Non-Linear Interference Management in Multi-Technology Communications Devices
审中-公开
基于Hammerstein结构的径向基函数神经网络方法与系统在多技术通信设备中的非线性干扰管理
- Patent Title: Methods and Systems for Radial Basis Function Neural Network With Hammerstein Structure Based Non-Linear Interference Management in Multi-Technology Communications Devices
- Patent Title (中): 基于Hammerstein结构的径向基函数神经网络方法与系统在多技术通信设备中的非线性干扰管理
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Application No.: US14849536Application Date: 2015-09-09
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Publication No.: US20160071007A1Publication Date: 2016-03-10
- Inventor: Sheng-Yuan TU , Farrokh Abrishamkar , lnsung Kang , Roberto Rimini
- Applicant: QUALCOMM Incorporated
- Main IPC: G06N3/08
- IPC: G06N3/08

Abstract:
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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