'Basis vectors' diaporamas de présentation

Outline

Outline. Signals Sampling Time and frequency domains Systems Filters Convolution MA, AR, ARMA filters System identification Graph theory FFT DSP processors Speech signal processing Data communications. DSP.

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Dense Object Recognition

Dense Object Recognition. 2. Template Matching. Face Detection. We will investigate face detection using a scanning window technique:. Think that this task sounds easy?. Training Data. Non-Faces. Faces. 800 random non-face regions 60x60, taken from same data as faces.

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5.4 Basis And Dimension

5.4 Basis And Dimension. Nonrectangular Coordinate Systems (1/4).

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MILLER INDICES

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Quantum Computing

Quantum Computing. Lecture on Linear Algebra. Sources: Angela Antoniu , Bulitko, Rezania, Chuang, Nielsen. Introduction to Quantum Mechanics. This can be found in Marinescu and in Chuang and Nielsen Objective To introduce all of the fundamental principles of Quantum mechanics

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Itay Hen

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Von Neumann to Bloom: Useful algorithmic techniques with vector spaces.

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Subspace Embeddings for the L1 norm with Applications Christian Sohler David Woodruff TU Dortmund IBM

Subspace Embeddings for the L1 norm with Applications Christian Sohler David Woodruff TU Dortmund IBM Almaden. Subspace Embeddings for the L1 norm with Applications to... Robust Regression and Hyperplane Fitting. Outline. Massive data sets Regression analysis Our results

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Ch. 2: Rigid Body Motions and Homogeneous Transforms

Ch. 2: Rigid Body Motions and Homogeneous Transforms. Updates. Sectioning Sections will start next week Labs Will begin the week of 2/19. number of groups TBD Office hours Me: MWTh, 4:00-5:00 and by appointment Ben & Shelten: by appointment Homework/policies. 02_01.

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Signal and Weight Vector Spaces

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Something noteworthy

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MOTIVATION

MOTIVATION. Chapter 4: Linear Algebra. Vector Spaces Algebra of Matrices Inverse Matrix. MOTIVATION. VECTOR SPACES: MOTIVATION.

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A quick example calculating the column space and the nullspace of a matrix.

A quick example calculating the column space and the nullspace of a matrix. . Isabel K. Darcy Mathematics Department Applied Math and Computational Sciences University of Iowa. Fig from knotplot.com. =. Determine the column space of A . Column space of A

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Basic Ray Tracing

Basic Ray Tracing. CMSC 435/634. Visibility Problem. Rendering: converting a model to an image Visibility : deciding which objects (or parts) will appear in the image Object- order OpenGL (later) Image-order Ray Tracing (now). Raytracing. Given Scene Viewpoint Viewplane

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C entered D iscrete F ractional F ourier T ransform & L inear C hirp S ignals

C entered D iscrete F ractional F ourier T ransform & L inear C hirp S ignals. Balu Santhanam & Juan G. Vargas- Rubio SPCOM Laboratory, Department of E.C.E. University of New Mexico, Albuquerque Email: bsanthan ,jvargas @ece.unm.edu. ABSTRACT.

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(1) Computer Science Department - University of Alcalá, SPAIN

A Numerically Efficient Technique for Orthogonalizing the Basis Functions Arising in the Solution of Electromagnetic Scattering Problems Using the CBFM Carlos Delgado (1) , Felipe Cátedra (1) and Raj Mittra (2). (1) Computer Science Department - University of Alcalá, SPAIN

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Linear algebra: matrix Eigen-value Problems

Linear algebra: matrix Eigen-value Problems. Eng. Hassan S. Migdadi. Part 3. Eigenvalue Problems. Eigenvalues and eigenvectors Vector spaces Linear transformations Matrix diagonalization. The Eigenvalue Problem. Consider a n x n matrix A Vector equation: Ax = l x

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Orthogonal Functions and Fourier Series

Orthogonal Functions and Fourier Series. Vector Spaces. Set of vectors Operations on vectors and scalars Vector addition: v 1 + v 2 = v 3 Scalar multiplication: s v 1 = v 2 Linear combinations: Closed under these operations Linear independence Basis Dimension. Vector Spaces.

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The integral of a vector field a(x) on a sphere

Matej Pavsic Home Page http://www-f1.ijs.si/~pavsic/. The integral of a vector field a(x) on a sphere. are coordinate. Let . be a vector field. Here . basis vectors, whilst. are local orthonormal basis vectors. Let us consider the integral. (1).

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Recap

Recap. Complex vector space : a set of abstract vectors or kets e.g. |v ? closed under addition, multiplication by scalar complex numbers, i.e. all vectors you can reach via addition/scalar multiplication are elements of the vector space. Zero vector plays a special role.

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