Nonnegative and Strictly Positive Linearization of Jacobi and Generalized Chebyshev Polynomials

In the theory of orthogonal polynomials, as well as in its intersection with harmonic analysis, it is an important problem to decide whether a given orthogonal polynomial sequence $$(P_n(x))_{n\in \mathbb {N}_0}$$ ( P n ( x ) ) n ∈ N 0 satisfies nonnegative linearization of products, i.e., the product of any two $$P_m(x),P_n(x)$$ P m ( x ) , P n ( x ) is a conical combination of the polynomials $$P_{|m-n|}(x),\ldots ,P_{m+n}(x)$$ P | m - n | ( x ) , … , P m + n ( x ) . Since the coefficients in the arising expansions are often of cumbersome structure or not explicitly available, such considerations are generally very nontrivial. Gasper (Can J Math 22:582–593, 1970) was able to determine the set V of all pairs $$(\alpha ,\beta )\in (-1,\infty )^2$$ ( α , β ) ∈ ( - 1 , ∞ ) 2 for which the corresponding Jacobi polynomials $$(R_n^{(\alpha ,\beta )}(x))_{n\in \mathbb {N}_0}$$ ( R n ( α , β ) ( x ) ) n ∈ N 0 , normalized by $$R_n^{(\alpha ,\beta )}(1)\equiv 1$$ R n ( α , β ) ( 1 ) ≡ 1 , satisfy nonnegative linearization of products. Szwarc (Inzell Lectures on Orthogonal Polynomials, Adv. Theory Spec. Funct. Orthogonal Polynomials, vol 2, Nova Sci. Publ., Hauppauge, NY pp 103–139, 2005) asked to solve the analogous problem for the generalized Chebyshev polynomials $$(T_n^{(\alpha ,\beta )}(x))_{n\in \mathbb {N}_0}$$ ( T n ( α , β ) ( x ) ) n ∈ N 0 , which are the quadratic transformations of the Jacobi polynomials and orthogonal w.r.t. the measure $$(1-x^2)^{\alpha }|x|^{2\beta +1}\chi _{(-1,1)}(x)\,\mathrm {d}x$$ ( 1 - x 2 ) α | x | 2 β + 1 χ ( - 1 , 1 ) ( x ) d x . In this paper, we give the solution and show that $$(T_n^{(\alpha ,\beta )}(x))_{n\in \mathbb {N}_0}$$ ( T n ( α , β ) ( x ) ) n ∈ N 0 satisfies nonnegative linearization of products if and only if $$(\alpha ,\beta )\in V$$ ( α , β ) ∈ V , so the generalized Chebyshev polynomials share this property with the Jacobi polynomials. Moreover, we reconsider the Jacobi polynomials themselves, simplify Gasper’s original proof and characterize strict positivity of the linearization coefficients. Our results can also be regarded as sharpenings of Gasper’s one.

New Approaches to the General Linearization Problem of Jacobi Polynomials Based on Moments and Connection Formulas

This article deals with the general linearization problem of Jacobi polynomials. We provide two approaches for finding closed analytical forms of the linearization coefficients of these polynomials. The first approach is built on establishing a new formula in which the moments of the shifted Jacobi polynomials are expressed in terms of other shifted Jacobi polynomials. The derived moments formula involves a hypergeometric function of the type 4F3(1), which cannot be summed in general, but for special choices of the involved parameters, it can be summed. The reduced moments formulas lead to establishing new linearization formulas of certain parameters of Jacobi polynomials. Another approach for obtaining other linearization formulas of some Jacobi polynomials depends on making use of the connection formulas between two different Jacobi polynomials. In the two suggested approaches, we utilize some standard reduction formulas for certain hypergeometric functions of the unit argument such as Watson’s and Chu-Vandermonde identities. Furthermore, some symbolic algebraic computations such as the algorithms of Zeilberger, Petkovsek and van Hoeij may be utilized for the same purpose. As an application of some of the derived linearization formulas, we propose a numerical algorithm to solve the non-linear Riccati differential equation based on the application of the spectral tau method.

Equations of periodic modes, which take into account features of the dynamics of their course in nonlinear automatic systems with computers in control system

In the article, based on the application of a continuous-discrete approach to the description of periodic modes that are possible in automatic systems with a control computer, equations are obtained that take into account the peculiarities of the dynamics of their flow in nonlinear systems of the noted class and provide an increase in the accuracy of calculating their parameters. This is achieved by taking into account the specifics of the structural diagram of the system under study by replacing the NOT system with harmonic linearization coefficients, which have correspondingly different formula expressions. The use of the proposed equations will make it possible to use the investigated modes more efficiently during the functioning of the system, or vice versa, it is guaranteed to get rid of them.

New Specific and General Linearization Formulas of Some Classes of Jacobi Polynomials

The main purpose of the current article is to develop new specific and general linearization formulas of some classes of Jacobi polynomials. The basic idea behind the derivation of these formulas is based on reducing the linearization coefficients which are represented in terms of the Kampé de Fériet function for some particular choices of the involved parameters. In some cases, the required reduction is performed with the aid of some standard reduction formulas for certain hypergeometric functions of unit argument, while, in other cases, the reduction cannot be done via standard formulas, so we resort to certain symbolic algebraic computation, and specifically the algorithms of Zeilberger, Petkovsek, and van Hoeij. Some new linearization formulas of ultraspherical polynomials and third-and fourth-kinds Chebyshev polynomials are established.

On Linearization Coefficients of $q$-Laguerre Polynomials

The linearization coefficient $\mathcal{L}(L_{n_1}(x)\dots L_{n_k}(x))$ of classical Laguerre polynomials $L_n(x)$ is known to be equal to the number of $(n_1,\dots,n_k)$-derangements, which are permutations with a certain condition. Kasraoui, Stanton and Zeng found a $q$-analog of this result using $q$-Laguerre polynomials with two parameters $q$ and $y$. Their formula expresses the linearization coefficient of $q$-Laguerre polynomials as the generating function for $(n_1,\dots,n_k)$-derangements with two statistics counting weak excedances and crossings. In this paper their result is proved by constructing a sign-reversing involution on marked perfect matchings.

Positivity and recursion formula of the linearization coefficients of Bessel polynomials

Positivity of the linearization coefficients for Bessel polynomials is proved in a more general case. The proof is based not only on a recursion formula (a formula similar to one given by Berg and Vignat) but also on giving an explicit triple sum formula. Moreover, this triple sum is simplified and a double sum formula for these linearization coefficients is given. In two general cases, this formula reduces indeed to either Atia and Zeng’s formula (M. J. Atia and J. Zeng, An explicit formula for the linearization coefficients of Bessel polynomials, Ramanujan J. 28(2) (2012) 211–221, doi: 10.1007/s11139-011-9348-4) or Berg and Vignat’s formulas in their proof of the positivity results about these coefficients (C. Berg and C. Vignat, Linearization coefficients of Bessel polynomials and properties of student [Formula: see text]-distributions, Constr. Approx. 27 (2008) 15–32).

Vibration analysis of beams subjected to random excitation by the dual criterion of equivalent linearizationVibration analysis of beams subjected to random excitation by the dual criterion of equivalent linearization

In this paper responses of beams subjected to random loading are analyzed by the dual approach of the equivalent linearization method. The external random loading is assumed to be a space-wise and time-wise white noise in which the exact solutions of the modal equations can be found. A system of nonlinear algebraic equations for linearization coefficients of the modal linearized system is obtained in a closed form and is solved by the fixed-point iteration method. Results obtained from the proposed dual criterion are compared with the exact solution and those obtained from other approaches including energy method, and conventional linearization method. It is observed that the solution obtained by the dual criterion is in good agreement with the exact solution, especially, in the case of strong nonlinearity of beam.

Characteristics Description of Electromagnetic Stiffness Compensator

This research presents the traction characteristic of the stiffness compensator using the odd polynomial. Due to the various components of the polynomial we can get any stiffness characteristics. The calculation of the polynomial coefficients is presented. For the representation of the characteristic in automatic control systems the harmonic linearization coefficients are obtained for the polynomial n-th degree, which corresponds accurately to the description of the precise method.