Classification of linear operators satisfying (Au,v)=(u,Av) or (Au,Av)=(u,v) on a vector space with indefinite scalar product

نویسندگان

چکیده

We classify all linear operators $A:V\to V$ satisfying $(Au,v)=(u,A^rv)$ and $(Au,A^rv)=(u,v)$ with $r=2,3,\dots$ on a complex, real, or quaternion vector space scalar product given by nonsingular symmetric, skew-symmetric, Hermitian, skew-Hermitian form.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

On Classification of Normal Operators in Real Spaces with Indefinite Scalar Product

A real finite dimensional space with indefinite scalar product having v − negative squares and v+ positive ones is considered. The paper presents a classification of operators that are normal with respect to this product for the cases min{v − , v+} = 1, 2. The approach to be used here was developed in the papers [1] and [2], where the similar classification was obtained for complex spaces with ...

متن کامل

On Indecomposable Normal Matrices in Spaces with Indefinite Scalar Product

Finite dimensional linear spaces (both complex and real) with indefinite scalar product [·, ·] are considered. Upper and lower bounds are given for the size of an indecomposable matrix that is normal with respect to this scalar product in terms of specific functions of v = min{v − , v+}, where v− (v+) is the number of negative (positive) squares of the form [x, x]. All the bounds except for one...

متن کامل

On Generalized Numerical Ranges of Operators on an Indefinite Inner Product Space

In this paper, numerical ranges associated to operators on an indefinite inner product space are investigated. Boundary generating curves, corners, shapes and computer generations of these sets are studied. In particular, the MurnaghanKippenhahn theorem for the classical numerical range is generalized.

متن کامل

Support Vector Machine Classification with Indefinite Kernels

We propose a method for support vector machine classification using indefinite kernels. Instead of directly minimizing or stabilizing a nonconvex loss function, our algorithm simultaneously computes support vectors and a proxy kernel matrix used in forming the loss. This can be interpreted as a penalized kernel learning problem where indefinite kernel matrices are treated as a noisy observation...

متن کامل

Canonical matrices of isometric operators on indefinite inner product spaces

We give canonical matrices of a pair (A,B) consisting of a nondegenerate form B and a linear operator A satisfying B(Ax,Ay) = B(x, y) on a vector space over F in the following cases: • F is an algebraically closed field of characteristic different from 2 or a real closed field, and B is symmetric or skew-symmetric; • F is an algebraically closed field of characteristic 0 or the skew field of qu...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Linear Algebra and its Applications

سال: 2021

ISSN: ['1873-1856', '0024-3795']

DOI: https://doi.org/10.1016/j.laa.2020.12.005