首页> 外文会议>International Work-Conference on Artificial Neural Networks(IWANN 2007); 20070620-22; San Sebastian(ES) >Sine Fitting Multiharmonic Algorithms Implemented by Artificial Neural Networks
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Sine Fitting Multiharmonic Algorithms Implemented by Artificial Neural Networks

机译:人工神经网络实现的正弦拟合多谐波算法

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A new method for spectral analysis, based on ADALINE artificial neural networks (ANNs), is proposed. The network is able to calculate accurately the fundamental frequency and the harmonic content of the input signal. This method is especially useful in high precision digital measurement systems in which periodical signals are involved, I.e. digital watt meters. Most of these system use spectrum analysis algorithms for the computation of the magnitudes of interest. The traditional spectrum analysis methods require synchronous sampling, which introduce limitations to the sampling circuitry. Sine-fitting multiharmonics algorithms resolve the hardware limitations concerning the synchronous sampling but have some limitations with regard to the phase of the array of samples. The new implementation of sine-fitting multiharmonics algorithms based in ANN, eliminates these limitations.
机译:提出了一种基于ADALINE人工神经网络的光谱分析新方法。该网络能够准确计算输入信号的基频和谐波含量。这种方法在涉及周期信号的高精度数字测量系统中特别有用,即数字电表。这些系统大多数使用频谱分析算法来计算感兴趣的幅度。传统的频谱分析方法需要同步采样,这会限制采样电路。正弦拟合多谐波算法解决了有关同步采样的硬件限制,但在样本阵列的相位方面有一些限制。基于ANN的正弦拟合多谐波算法的新实现消除了这些限制。

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