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1.
Higher-order spectral analysis techniques are often used to identify nonlinearities in complex dynamical systems. More specifically, the auto- and cross-bispectrum have proven to be useful tools in testing for the presence of quadratic nonlinearities based on knowledge of a system's input and output. In this paper, analytical expressions for the auto- and cross-bispectrum are developed using a Volterra functional approach under the assumption of a zero-mean, stationary Gaussian input; proper simplifications are presented when the whiteness of the input signal is also imposed. These formulae show the contributions of the bispectrum in terms of the system frequency response function and elementary physical properties of the system. Simulations based on a stochastic numerical integration technique accompany the analytical solutions for a mechanical mass–spring–damper system possessing quadratic damping and stiffness coefficients and subjected to Gaussian white noise excitation. Subsequent estimates of the bispectrum based on the simulated signals show excellent agreement with theory. These results show how modes may interact nonlinearly producing intermodulation components at the sum and/or difference frequency of the fundamental modes of oscillation. The presence and extent of nonlinear interactions between frequency components are identified. Advantages of using higher-order spectra techniques will be revealed and pertinent conclusions will be outlined.  相似文献
2.
This paper presents results relating to the measurement of differential and integral nonlinearity of ADCs using the histogram method with white Gaussian noise as the stimulus signal. We specify the optimum noise power of the generator, in the sense of number of samples minimisation, as a function of the converter range and resolution. An expression of tolerance interval as a function of the number of samples acquired given a certain confidence level is presented both for the determination of transition levels (INL) and quantization intervals (DNL). Experimental and simulation results concerning the characterization of a 12-bit PC acquisition board are shown.  相似文献
3.
拉格朗日乘子神经网络是一种适合于求解一般约束问题的神经网络。网络运行中附加动量项和引入逐渐衰减的高斯噪声。附加动量项方法能减少震荡时间,提高网络的收敛速度。高斯噪声能避免神经网络收敛于假吸引子,改善全局寻优能力。用该方法解决飞机总体参数优化问题。数值结果表明,算法的稳定性、全局寻优性、约束的满足程度好,同时拉氏乘子可以帮助进行最优设计结果的灵敏度分析。  相似文献
4.
In this paper, a new adaptive control approach is presented for multivariate nonlinear non-Gaussian systems with unknown models. A more general and systematic statistical measure, called (h,?)(h,?)-entropy, is adopted here to characterize the uncertainty of the considered systems. By using the “sliding window” technique, the non-parameter estimate of the (h,?)(h,?)-entropy is formulated. Then, the improved neuron based controllers are developed for multivariate nonlinear non-Gaussian systems by minimizing the entropies of the tracking errors in closed loops. The condition to guarantee the strictly decreasing entropy of tracking error is presented. Moreover, the convergence in the mean-square sense has been analyzed for all the weights in the neural controllers. Finally, the comparative simulation results are presented to show that the performance of the proposed algorithm is superior to that of PID control strategy.  相似文献
5.
结合成像模型,从数学角度分析了噪声对重构结果的影响,结合POCS算法,仿真了常见成像模型中噪声对重构结果的影响。通过MATLAB软件仿真获取低分辨率图像序列集,并对低分辨率图像施加噪声获取带有噪声的低分辨率图像集,再借助算法获取高分辨率图像。根据实际情况的不同,分别仿真分析了不同程度的高斯噪声和乘性噪声以及椒盐噪声对最终重构结果的影响。研究结果表明:不论何种噪声,其对重构结果的影响趋势基本一致,即较小噪声对于重构结果影响较小,但随着噪声的增加,图像质量严重退化,重构结果中信噪比相对于原始图像下降更快,图像质量更差;另一方面在相同的信噪比情况下,高斯噪声对于重构结果的影响最大。  相似文献
6.
This paper proposes a spatially denoising algorithm using filtering-based noise estimation for an image corrupted by Gaussian noise.The proposed algorithm consists of two stages:estimation and elimination of noise density.To adaptively deal with variety of the noise amount,a noisy input image is firstly filtered by a lowpass filter.Standard deviation of the noise is computed from different images between the noisy input and its filtered image.In addition,a modified Gaussian noise removal filter based on the local statistics such as local weighted mean,local weighted activity and local maximum is used to control the degree of noise suppression.Experiments show the effectiveness of the proposed algorithm.  相似文献
7.
We present a preliminary design and experimental results of a Gaussian noise reduction method for ultrasound images. Our method utilizes a Wiener filtering algorithm with pseudo-inverse technique. The method is capable of solving the Gaussian noise problem in ultrasound image by setup a constant dB of noise function. The key idea of the Wiener filtering algorithm is to process the given ultrasound signal by making the filtering less sensitive to slight changes in input conditions. In this paper, we investigate the possibility of employing this approach for pre-processing ultrasound image application. The application of the proposed method for reducing Gaussian noise is demonstrated by four examples. Meanwhile, we also made the comparisons with median filter, mean filter and adaptive filter; the results reveal that the proposed method has the best noise filtering capability than other three methods. The results also show that the proposed method produces recovery images with quiet high peak-signal-to-noise ratio.  相似文献
8.
李雪  江旻珊 《光学仪器》2018,40(1):28-38
图像清晰度评价函数是评价各类成像系统成像质量的一个关键函数,为找到合适的图像清晰度评价算法,采用MATLAB软件对16种适用于光学显微成像系统的清晰度评价函数进行仿真,定量分析了不同算法的灵敏度、单峰性、无偏性以及运算速度。实验表明:Laplacian函数具有较高的单峰性、无偏性和灵敏度;存在高斯噪声时,Brenner函数、Tenengrad函数和基于Prewitt算子的函数以及中值滤波-离散余弦函数稳定性好;而存在椒盐噪声时,Roberts函数综合性能最优。  相似文献
9.
A new method based on nonlinear least squares regression (NLLSR) is formulated to estimate signal‐to‐noise ratio (SNR) of scanning electron microscope (SEM) images. The estimation of SNR value based on NLLSR method is compared with the three existing methods of nearest neighbourhood, first‐order interpolation and the combination of both nearest neighbourhood and first‐order interpolation. Samples of SEM images with different textures, contrasts and edges were used to test the performance of NLLSR method in estimating the SNR values of the SEM images. It is shown that the NLLSR method is able to produce better estimation accuracy as compared to the other three existing methods. According to the SNR results obtained from the experiment, the NLLSR method is able to produce approximately less than 1% of SNR error difference as compared to the other three existing methods.  相似文献
10.
A new technique based on cubic spline interpolation with Savitzky–Golay noise reduction filtering is designed to estimate signal‐to‐noise ratio of scanning electron microscopy (SEM) images. This approach is found to present better result when compared with two existing techniques: nearest neighbourhood and first‐order interpolation. When applied to evaluate the quality of SEM images, noise can be eliminated efficiently with optimal choice of scan rate from real‐time SEM images, without generating corruption or increasing scanning time.  相似文献
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