In the context of field extensions, the concept of a "dual basis" typically applies within the framework of vector spaces and linear algebra.

The Frobenius normal form, also known as the Frobenius form or the rational canonical form, is a specific way to represent a linear transformation or a matrix that highlights its structure in a form that can be easily understood and analyzed, particularly regarding information about its eigenvalues and invariant factors.

A glossary of linear algebra typically includes key terms and concepts that are fundamental to the study and application of linear algebra. Here’s a list of some important terms you might find in such a glossary: ### Glossary of Linear Algebra 1. **Vector**: An element of a vector space; often represented as a column or row of numbers. 2. **Matrix**: A rectangular array of numbers arranged in rows and columns.

Compressed sensing (CS) is a technique in signal processing that enables the reconstruction of a signal from a small number of samples. It leverages the idea that many signals are sparse or can be sparsely represented in some basis, meaning that they contain significant information in far fewer dimensions than they are originally represented in. ### Key Concepts of Compressed Sensing: 1. **Sparsity**: A signal is considered sparse if it has a representation in a transformed domain (e.g.

In mathematics, particularly in linear algebra, a conformable matrix refers to matrices that can be operated on together under certain operations, typically matrix addition or multiplication. For two matrices to be conformable for addition, they must have the same dimensions (i.e., the same number of rows and columns). For multiplication, the number of columns in the first matrix must match the number of rows in the second matrix.

A constant-recursive sequence is a type of sequence defined by a recurrence relation that is constant in nature, meaning that each term is generated based on a fixed number of previous terms and/or constant values. In other words, the sequence is defined using a recurrence that repeatedly applies the same operation without changing its parameters over time.

A **controlled invariant subspace** is a concept from control theory and linear algebra that pertains to the behavior of dynamical systems. In the context of linear systems, it often refers to subspaces of the state space that are invariant under the action of the system's dynamics when a control input is applied.

A **convex cone** is a fundamental concept in mathematics, particularly in linear algebra and convex analysis.

In the context of linear algebra and functional analysis, a **cyclic subspace** is a specific type of subspace generated by the action of a linear operator on a particular vector. Often discussed in relation to operators on Hilbert spaces or finite-dimensional vector spaces, a cyclic subspace can be defined as follows: Let \( A \) be a linear operator on a vector space \( V \), and let \( v \in V \) be a vector.

A defective matrix is a square matrix that does not have a complete set of linearly independent eigenvectors. This means that its algebraic multiplicity (the number of times an eigenvalue occurs as a root of the characteristic polynomial) is greater than its geometric multiplicity (the number of linearly independent eigenvectors associated with that eigenvalue). In other words, a matrix is considered defective if it cannot be diagonalized.

A **definite quadratic form** refers to a specific type of quadratic expression in multiple variables that has particular properties regarding the sign of its output. In mathematical terms, a quadratic form can generally be represented as: \[ Q(\mathbf{x}) = \mathbf{x}^T A \mathbf{x} \] where: - \(\mathbf{x}\) is a vector of variables (e.g., \((x_1, x_2, ...

In linear algebra and functional analysis, the concept of a dual basis is tied to the idea of dual spaces.

Eigenplane is a technique related to the fields of machine learning and computer vision that typically involves dimensionality reduction and representation learning. It is often used to represent complex data by finding a lower-dimensional space that captures the essential features of the data while retaining its important characteristics.

Eigenvalue perturbation refers to the study of how the eigenvalues and eigenvectors of a matrix change when the matrix is slightly altered or perturbed. This concept is particularly important in linear algebra, numerical analysis, and various applied fields such as physics and engineering, where systems are often subject to small variations.

The Schmidt decomposition is a mathematical technique used in quantum mechanics and quantum information theory to express a bipartite quantum state in a particularly useful form. It is analogous to the singular value decomposition in linear algebra. For a bipartite quantum system, which consists of two subsystems (commonly referred to as systems A and B), the Schmidt decomposition allows us to write a pure state \(|\psi\rangle\) in such a way that it identifies the correlations between the two subsystems.

A seminorm is a mathematical concept used in functional analysis, particularly in the study of vector spaces. It generalizes the idea of a norm but is less restrictive.

The term "Fangcheng" (方程) in mathematics is Chinese for "equation." An equation is a mathematical statement that asserts the equality of two expressions, typically containing one or more variables. Equations play a fundamental role in various branches of mathematics and are used to solve problems across different fields, such as algebra, calculus, and physics.

A finite von Neumann algebra is a special type of von Neumann algebra that satisfies certain properties related to its structure and its trace. Von Neumann algebras are a class of *-algebras of bounded operators on a Hilbert space that are closed in the weak operator topology. They play a central role in functional analysis and quantum mechanics.

In linear algebra, a **frame** is a concept that generalizes the idea of a basis in a vector space. While a basis is a set of linearly independent vectors that spans the vector space, a frame can include vectors that are not necessarily independent and may provide redundancy. This redundancy is beneficial in various applications, particularly in signal processing and data analysis.

The Fredholm alternative is a principle in functional analysis that relates to the solvability of certain linear operator equations, particularly in the context of compact operators on Banach spaces or Hilbert spaces. It is especially relevant when dealing with integral equations and partial differential equations.