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Filtering and smoothing of financial data using Wavelets: New trends in filtering and smoothing - Softcover
Synopsis
As temporal data are of growing importance hence require to support new trends for filtering and smoothing. The main goal of this work is to explore new smoothing techniques like wavelet filters in place of traditional moving averages and regression methods, etc for temporal data for further decision making processes like forecasting, similarities search and clustering. Temporal applications are increasingly popular methods for studying a wide range of databases including sensor, weather, stock exchange, seismic and atomic, etc. Time series, a common form of temporal data, are mostly contaminated with noise and outliers. The direct operation and analysis on these types of raw data, may easily lead to wrong decisions. The selection of appropriate smoothing techniques is the pivotal point to reach to the correct conclusions. In this work, the main task has been to select the best possible smoothing technique for selection of features of time series to perform various tasks.
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About the Author
Dr. M. Afzal Saleemi completed his Ph.D. in Computer Science in 2007 from University of Karachi. He is working as head of Computer Science Department National University of Sciences and Technology, NUST (PMA). His areas of interests are Wavelets, Data and Knowledge Engineering, Data mining, Database Management System, and Soft computing.
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Filtering and smoothing of financial data using Wavelets
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LAP LAMBERT Academic Publishing Jan 2012, 2012
ISBN 10: 384734109X
ISBN 13: 9783847341093
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -As temporal data are of growing importance hence require to support new trends for filtering and smoothing. The main goal of this work is to explore new smoothing techniques like wavelet filters in place of traditional moving averages and regression methods, etc for temporal data for further decision making processes like forecasting, similarities search and clustering. Temporal applications are increasingly popular methods for studying a wide range of databases including sensor, weather, stock exchange, seismic and atomic, etc. Time series, a common form of temporal data, are mostly contaminated with noise and outliers. The direct operation and analysis on these types of raw data, may easily lead to wrong decisions. The selection of appropriate smoothing techniques is the pivotal point to reach to the correct conclusions. In this work, the main task has been to select the best possible smoothing technique for selection of features of time series to perform various tasks. 128 pp. Englisch. Seller Inventory # 9783847341093
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Filtering and smoothing of financial data using Wavelets : New trends in filtering and smoothing
Published by
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 384734109X
ISBN 13: 9783847341093
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As temporal data are of growing importance hence require to support new trends for filtering and smoothing. The main goal of this work is to explore new smoothing techniques like wavelet filters in place of traditional moving averages and regression methods, etc for temporal data for further decision making processes like forecasting, similarities search and clustering. Temporal applications are increasingly popular methods for studying a wide range of databases including sensor, weather, stock exchange, seismic and atomic, etc. Time series, a common form of temporal data, are mostly contaminated with noise and outliers. The direct operation and analysis on these types of raw data, may easily lead to wrong decisions. The selection of appropriate smoothing techniques is the pivotal point to reach to the correct conclusions. In this work, the main task has been to select the best possible smoothing technique for selection of features of time series to perform various tasks. Seller Inventory # 9783847341093
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Filtering and smoothing of financial data using Wavelets
Published by
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 384734109X
ISBN 13: 9783847341093
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Saleemi AfzalDr. M. Afzal Saleemi completed his Ph.D. in Computer Science in 2007 from University of Karachi. He is working as head of Computer Science Department National University of Sciences and Technology, NUST (PMA). His areas . Seller Inventory # 5511249
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Filtering and smoothing of financial data using Wavelets
Published by
LAP LAMBERT Academic Publishing Jan 2012, 2012
ISBN 10: 384734109X
ISBN 13: 9783847341093
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -As temporal data are of growing importance hence require to support new trends for filtering and smoothing. The main goal of this work is to explore new smoothing techniques like wavelet filters in place of traditional moving averages and regression methods, etc for temporal data for further decision making processes like forecasting, similarities search and clustering. Temporal applications are increasingly popular methods for studying a wide range of databases including sensor, weather, stock exchange, seismic and atomic, etc. Time series, a common form of temporal data, are mostly contaminated with noise and outliers. The direct operation and analysis on these types of raw data, may easily lead to wrong decisions. The selection of appropriate smoothing techniques is the pivotal point to reach to the correct conclusions. In this work, the main task has been to select the best possible smoothing technique for selection of features of time series to perform various tasks.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch. Seller Inventory # 9783847341093
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Filtering and smoothing of financial data using Wavelets | New trends in filtering and smoothing
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ISBN 10: 384734109X
ISBN 13: 9783847341093
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Taschenbuch. Condition: Neu. Filtering and smoothing of financial data using Wavelets | New trends in filtering and smoothing | Afzal Saleemi (u. a.) | Taschenbuch | 128 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783847341093 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 106647012
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Filtering and smoothing of financial data using Wavelets : New trends in filtering and smoothing
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LAP LAMBERT Academic Publishing, 2012
ISBN 10: 384734109X
ISBN 13: 9783847341093
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Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | As temporal data are of growing importance hence require to support new trends for filtering and smoothing. The main goal of this work is to explore new smoothing techniques like wavelet filters in place of traditional moving averages and regression methods, etc for temporal data for further decision making processes like forecasting, similarities search and clustering. Temporal applications are increasingly popular methods for studying a wide range of databases including sensor, weather, stock exchange, seismic and atomic, etc. Time series, a common form of temporal data, are mostly contaminated with noise and outliers. The direct operation and analysis on these types of raw data, may easily lead to wrong decisions. The selection of appropriate smoothing techniques is the pivotal point to reach to the correct conclusions. In this work, the main task has been to select the best possible smoothing technique for selection of features of time series to perform various tasks. Seller Inventory # 11882391/1
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Filtering and smoothing of financial data using Wavelets: New trends in filtering and smoothing
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LAP LAMBERT Academic Publishing, 2012
ISBN 10: 384734109X
ISBN 13: 9783847341093
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