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首页> 外文期刊>British Journal of Applied Science and Technology >Optimal Spike Detection Technique Based onAmplitude Threshold
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Optimal Spike Detection Technique Based onAmplitude Threshold

机译:基于幅度阈值的最优峰值检测技术

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Spike detection as the first basic step is very important in analysing and classification of data, since the quality of resulting data depends crucially on a particular detection technique used. This paper presents the optimal spike detection technique based on amplitude threshold on a band pass filtered signal. Comparisons were made on four different filtered signals: voltage of the entire signal, power of the entire signal, voltage moving average and power moving average of the signal. MATLAB was used to generate six different realistic simulations with varying signal to noise ratio which resembles that of a real dataset. The six different simulations contain ten samples each. For each simulated signal, only one type of spike shape was used with same firing frequency following a Poisson distribution. The duration of the simulation was equal in all cases with the signal to noise ratio defined as the amplitude of the spikes normalized by the noise level. Also, the threshold for spike detection was calculated based on the estimation of the standard deviation of noise; the area under the receiver operating characteristic curve and statistical analysis of data were used to quantify their performance. The major finding is that the voltage technique superseded all other techniques mentioned above both in high and low signal to noise ratio. When voltage was compared with power, voltage moving average (vma) and power moving average (pma), it was observed that p (0.0022) 0.05 and h = 1. This means that the test rejects the null hypothesis of equal medians. When power was compared with vma using Mann-Whitney U-Test, it was observed that p (0.0043) 0.05 with h = 1, implying that the test rejects the null hypothesis of equal medians but when power was compared with pma, it was observed that p (0.1320) 0.05 with h = 0, also implying that the test accepts the null hypothesis of equal medians. For comparison of vma and pma, it was observed that p (0.6991) 0.05 with h = 0 which presents that the test accepts the null hypothesis of equal medians. However, is clear that voltage technique is the optimal spike detection technique based on amplitude threshold.
机译:峰值检测作为第一步基本步骤在数据的分析和分类中非常重要,因为结果数据的质量主要取决于所使用的特定检测技术。本文提出了一种基于幅度阈值的带通滤波信号最优尖峰检测技术。对四个不同的滤波信号进行了比较:整个信号的电压,整个信号的功率,信号的电压移动平均值和功率移动平均值。 MATLAB用于生成六种不同的逼真的仿真,其信噪比与真实数据集的信噪比不同。六个不同的模拟每个包含十个样本。对于每个模拟信号,仅使用一种类型的尖峰形状,并且具有遵循泊松分布的相同触发频率。在所有情况下,仿真持续时间均相等,信噪比定义为通过噪声水平归一化的尖峰幅度。另外,基于噪声的标准偏差的估计来计算尖峰检测的阈值。接收器工作特性曲线下方的区域和数据的统计分析用于量化其性能。主要发现是电压技术在高信噪比和低信噪比方面都取代了上面提到的所有其他技术。将电压与功率,电压移动平均值(vma)和功率移动平均值(pma)进行比较时,观察到p(0.0022)<0.05且h =1。这意味着该检验拒绝了均值相等的零假设。当使用Mann-Whitney U检验将功效与vma进行比较时,观察到在h = 1时p(0.0043)<0.05,这意味着检验拒绝了中位数相等的零假设,但是当功效与pma进行比较时,观察到在h = 0时p(0.1320)> 0.05,也暗示该检验接受相等中位数的原假设。为了比较vma和pma,观察到p(0.6991)> 0.05,且h = 0,这表明检验接受了相等中位数的零假设。但是,很明显,电压技术是基于幅度阈值的最佳尖峰检测技术。

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