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Book
Partial update least-square adaptive filtering
Authors: ---
ISBN: 1627052321 Year: 2014 Publisher: [San Rafael, California] : Morgan & Claypool Publishers,

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Abstract

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.

Theory of the combination of observations least subject to errors
Authors: ---
ISBN: 0898713471 Year: 1995 Volume: 11 Publisher: Philadelphia, Pa Society for Industrial and Applied Mathematics


Book
Applying partial least squares in tourism and hospitality research
Authors: --- ---
ISBN: 178756701X 1787566994 9781787567016 9781787566996 1787567001 1787567028 9781787567009 Year: 2019 Publisher: Bingley, UK Emerald Publishing Limited

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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.

Recent advances in total least squares techniques and errors-in-variables modeling
Authors: --- ---
ISBN: 0898713935 Year: 1997 Publisher: Philadelphia (Pa.) SIAM


Book
Running regressions : a practical guide to quantitative research in economics, finance and development studies
Authors: --- ---
ISBN: 1139698478 1139861468 0511814836 Year: 2009 Publisher: New York : Cambridge University Press,

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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.


Book
Statistical learning with sparsity : the lasso and generalizations
Authors: --- --- --- --- --- et al.
ISSN: 09606696 ISBN: 9781498712163 1498712169 Year: 2015 Volume: 143 Publisher: Boca Raton CRC Press, Taylor & Francis Group

The total least squares problem: computational aspects and analysis
Authors: ---
ISBN: 0898712750 Year: 1991 Volume: 9 Publisher: Philadelphia, Pa Society for Industrial and Applied Mathematics

Numerical methods for least squares problems
Author:
ISBN: 0898713609 Year: 1996 Publisher: Philadelphia : Society for Industrial and Applied Mathematics,


Book
New Perspectives in Partial Least Squares and Related Methods
Authors: --- --- --- ---
ISBN: 1461482828 1461482836 Year: 2013 Publisher: New York, NY : Springer New York : Imprint: Springer,

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Abstract

New Perspectives in Partial Least Squares and Related Methods shares original, peer-reviewed research from presentations during the 2012 partial least squares methods meeting (PLS 2012). This was the 7th meeting in the series of PLS conferences and the first to take place in the USA. PLS is an abbreviation for Partial Least Squares and is also sometimes expanded as projection to latent structures. This is an approach for modeling relations between data matrices of different types of variables measured on the same set of objects. The twenty-two papers in this volume, which include three invited contributions from our keynote speakers, provide a comprehensive overview of the current state of the most advanced research related to PLS and related methods. Prominent scientists from around the world took part in PLS 2012 and their contributions covered the multiple dimensions of the partial least squares-based methods. These exciting theoretical developments ranged from partial least squares regression and correlation, component based path modeling to regularized regression and subspace visualization. In following the tradition of the six previous PLS meetings, these contributions also included a large variety of PLS approaches such as PLS metamodels, variable selection, sparse PLS regression, distance based PLS, significance vs. reliability, and non-linear PLS. Finally, these contributions applied PLS methods to data originating from the traditional econometric/economic data to genomics data, brain images, information systems, epidemiology, and chemical spectroscopy. Such a broad and comprehensive volume will also encourage new uses of PLS models in work by researchers and students in many fields.

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