Listing 1 - 10 of 44 | << page >> |
Sort by
|
Choose an application
Adaptive filters play an important role in the fields related to digital signal processing and communication, such as system identification, noise cancellation, channel equalization, and beamforming. In practical applications, the computational complexity of an adaptive filter is an important consideration. The Least Mean Square (LMS) algorithm is widely used because of its low computational complexity (O(N)) and simplicity in implementation. The least squares algorithms, such as Recursive Least Squares (RLS), Conjugate Gradient (CG), and Euclidean Direction Search (EDS), can converge faster and have lower steady-state mean square error (MSE) than LMS. However, their high computational complexity (O(N2)) makes them unsuitable for many real-time applications. A well-known approach to controlling computational complexity is applying partial update (PU) method to adaptive filters. A partial update method can reduce the adaptive algorithm complexity by updating part of the weight vector instead of the entire vector or by updating part of the time. In the literature, there are only a few analyses of these partial update adaptive filter algorithms. Most analyses are based on partial update LMS and its variants. Only a few papers have addressed partial update RLS and Affine Projection (AP). Therefore, analyses for PU least-squares adaptive filter algorithms are necessary and meaningful.
Adaptive filters --- Least squares. --- Method of least squares --- Squares, Least --- Curve fitting --- Geodesy --- Mathematical statistics --- Mathematics --- Probabilities --- Triangulation --- Filters, Adaptive --- Electric filters --- Design and construction.
Choose an application
Mathematical statistics --- Least squares. --- Error analysis (Mathematics) --- Least squares --- #TELE:SISTA --- Method of least squares --- Squares, Least --- Curve fitting --- Geodesy --- Mathematics --- Probabilities --- Triangulation --- Errors, Theory of --- Instrumental variables (Statistics) --- Numerical analysis --- Statistics
Choose an application
Ten chapters discuss key aspects of advanced PLS analysis and its practical applications, covering new guidelines and improvements in the use of PLS-PM as well as various individual topics.
Least squares. --- Structural equation modeling. --- SEM (Structural equation modeling) --- Multivariate analysis --- Factor analysis --- Regression analysis --- Path analysis (Statistics) --- Method of least squares --- Squares, Least --- Curve fitting --- Geodesy --- Mathematical statistics --- Mathematics --- Probabilities --- Triangulation --- Hospitality industry --- Research --- E-books --- Service industries
Choose an application
Filtering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing complexity are analyzed and solved within this framework, starting with the Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background topics, including linear matrix algebra and linear system theory, are covered, followed by different estimation and identification methods in the state-space model. With end-of-chapter exercises, MATLAB simulations and numerous illustrations, this book will appeal to graduate students and researchers in electrical, mechanical and aerospace engineering. It is also useful for practitioners. Additional resources for this title, including solutions for instructors, are available online at www.cambridge.org/9780521875127.
Filters (Mathematics) --- System identification. --- Filtres (Mathématiques) --- Systèmes, Identification des --- Mathematics --- Identification, System --- System analysis --- Least squares. --- Method of least squares --- Squares, Least --- Curve fitting --- Geodesy --- Mathematical statistics --- Probabilities --- Triangulation
Choose an application
Error analysis (Mathematics) --- Least squares --- Academic collection --- #TELE:SISTA --- Method of least squares --- Squares, Least --- Curve fitting --- Geodesy --- Mathematical statistics --- Mathematics --- Probabilities --- Triangulation --- Errors, Theory of --- Instrumental variables (Statistics) --- Numerical analysis --- Statistics --- Congresses
Choose an application
Running Regressions introduces first-year social science undergraduates, particularly those studying economics and business, to the practical aspects of simple regression analysis, without adopting an esoteric, mathematical approach. It shows that statistical analysis can be simultaneously straightforward, useful and interesting, and can deal with topical, real-world issues. Each chapter introduces an economic theory or idea by relating it to an issue of topical interest, and explains how data and econometric analysis can be used to test it. The book can be used as a self-standing text or to supplement conventional econometric texts. It is also ideally suited as a guide to essays and project work.
Econometrics. --- Least squares. --- Regression analysis. --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Method of least squares --- Squares, Least --- Curve fitting --- Geodesy --- Mathematical statistics --- Mathematics --- Probabilities --- Triangulation --- Economics, Mathematical --- Statistics
Choose an application
Mathematical statistics --- Least squares --- Linear models (Statistics) --- Proof theory --- Mathematical statistics. --- Least squares. --- Proof theory. --- Logic, Symbolic and mathematical --- Models, Linear (Statistics) --- Mathematical models --- Statistics --- Method of least squares --- Squares, Least --- Curve fitting --- Geodesy --- Mathematics --- Probabilities --- Triangulation --- Statistical inference --- Statistics, Mathematical --- Sampling (Statistics) --- Statistical methods
Choose an application
Mathematical statistics --- Échantillonnage --- Sampling --- 519.235 --- Least squares --- Regression analysis --- #TELE:SISTA --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Method of least squares --- Squares, Least --- Curve fitting --- Geodesy --- Mathematics --- Probabilities --- Triangulation --- Statistics of dependent variables. Contingency tables --- Least squares. --- Regression analysis. --- 519.235 Statistics of dependent variables. Contingency tables
Choose an application
Operational research. Game theory --- Moindres carrés --- Least squares --- Academic collection --- #TELE:SISTA --- 519.6 --- Method of least squares --- Squares, Least --- Curve fitting --- Geodesy --- Mathematical statistics --- Mathematics --- Probabilities --- Triangulation --- Computational mathematics. Numerical analysis. Computer programming --- Least squares. --- 519.6 Computational mathematics. Numerical analysis. Computer programming --- Moindres carrés
Choose an application
Numerical analysis --- Mathematical statistics --- Equations, Simultaneous --- Least squares --- Moindres carrés --- Numerical solutions --- Least squares. --- Numerical solutions. --- 519.65 --- -Least squares --- #TELE:SISTA --- Method of least squares --- Squares, Least --- Curve fitting --- Geodesy --- Mathematics --- Probabilities --- Triangulation --- Simultaneous equations --- Approximation. Interpolation --- 519.65 Approximation. Interpolation --- Moindres carrés --- Numerical calculations --- Calculs numériques --- Moindres carrés. --- Calculs numériques. --- Analyse numérique. --- Algèbre linéaire. --- Algebras, Linear
Listing 1 - 10 of 44 | << page >> |
Sort by
|