Wavelet Filtering in Shock Stochastic Systems with High Availability

Sinitsyn Igor Nikolaevich, Sinitsyn Vladimir Igorevich, Korepanov Edward Rudolfovich, Konashenkova Tatyana Dmitirievna
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Abstract

For filtering problems in StSHA under nonGaussian ShD methodological and algorithmically WL support is developed. 3 types of filters are considered: KBF (WLKBF), LPF (WLLPF) and SOLF (WLSOLF). These filters have the following advantages: on-line regime, high accuracy and possibility of algorithmically description of complex ShD. Wavelet filter modifications are based on Galerkin method and Haar wavelet expansions. WLF unlike KBF, LPF and SOLF do not need to integrate system of ordinary differential Eqs. These filters must solve system of linear algebraic Eqs with constant coefficients. KBF (WLKBF) and SOLF (WLSOLF) are recommended for StSHA with additive ShD whereas LPF (WLLPF) are recommended for StSHA with parametric and additive ShD. Basic applications are: on-line identification and calibration of nonstationary processes in StSHA of ShD. Methods are illustrated by example of 3 dimensional differential linear information control system at complex ShD. Basic algorithms and error analysis for KBF (WLKBF) and LPF (WLLPF) are presented and 15 Figure; illustrate filters peculiarities for small and fin damping. These filters allow to estimate the accumulation effects for systematic and random errors. Results may be generalized for filtration, extrapolation with interpolation problems in StSHA and multiple ShD.
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高可用性冲击随机系统的小波滤波
对于非高斯ShD条件下StSHA中的滤波问题,开发了支持WL的方法和算法。考虑了三种类型的滤波器:KBF (WLKBF), LPF (WLLPF)和SOLF (WLSOLF)。这些滤波器具有在线状态、精度高、可以对复杂的ShD进行算法描述等优点。小波滤波器的改进是基于伽辽金方法和哈尔小波展开。与KBF、LPF和SOLF不同,WLF不需要积分常微分方程系统。这些滤波器必须求解常系数线性代数方程组。对于具有可加ShD的StSHA,建议使用KBF (WLKBF)和SOLF (WLSOLF),而对于具有参数ShD和可加ShD的StSHA,建议使用LPF (WLLPF)。基本应用是:ShD的StSHA非平稳过程的在线识别和校准。以三维微分线性信息控制系统为例,说明了该方法的有效性。给出了KBF (WLKBF)和LPF (WLLPF)的基本算法和误差分析。说明小阻尼和翅片阻尼滤波器的特性。这些滤波器允许估计系统误差和随机误差的累积效应。结果可推广到StSHA和多重ShD的过滤、插值外推问题。
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