The paper examines spectral methods based on classical orthogonal polynomials for solving problems of digital information processing. Based on Jacobi polynomials, signal approximation methods are built to identify objects in the natural environment. Based on Chebyshev-Laguerre polynomials, methods of filtering multiplicative signal noises in linear filter models are proposed. Numerical experiments on model problems were conducted.

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