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Application of neural network for digital recursive filter design

机译:神经网络在数字递归滤波器设计中的应用

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Digital Signal Processing is an advanced technology that will determine the direction of science and technology in the next centuries. One of the main direction of digital signals processing is digital filters, which in the most cases have advantages over analog filters. Currently there are various methods of filter analysis and design. In this work, for synthesis of all types of recursive filters (low pass, high pass, bandwidth, band stop) is used a neural network. The main objective of filter synthesis is to find the filter coefficients. These filter coefficients define the filter transfer function. Using an iterative procedure of the neural network such as Backpropagation algorithm, on base of Visual C++ software was developed the program, which designs recursive filters with required characteristics. This is particularly important for the designing of the new correcting filters characteristics, the purpose of which is to reduce the unwanted noises in the measurement signal.
机译:数字信号处理是一项先进的技术,它将决定未来几个世纪科学技术的方向。数字信号处理的主要方向之一是数字滤波器,在大多数情况下,它们比模拟滤波器具有优势。当前,有多种过滤器分析和设计方法。在这项工作中,为了合成所有类型的递归滤波器(低通,高通,带宽,带阻),使用了神经网络。滤波器合成的主要目的是找到滤波器系数。这些滤波器系数定义了滤波器传递函数。该程序使用诸如反向传播算法之类的神经网络迭代程序,在Visual C ++软件的基础上开发了该程序,该程序设计了具有所需特性的递归滤波器。这对于设计新的校正滤波器特性特别重要,其目的是减少测量信号中的有害噪声。

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