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APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS期刊基本信息

  • 簡稱:APPL COMPUT HARMON A
  • 大類:數(shù)學
  • 小類:應用數(shù)學
  • ISSN:1063-5203
  • IF值:2.964
  • 周期:Bimonthly
  • 是否SCI:SCI/SCIE
  • 是否OA:No
  • 出版地:UNITED STATES
  • 年文章數(shù):49
  • 審稿速度:較慢,6-12周
  • 平均錄用比例:較易
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APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS中文簡介

應用和計算諧波分析(據(jù))是一個跨學科期刊發(fā)表高質量的論文在數(shù)學科學的所有領域相關諧波分析的應用和計算方面,特別強調創(chuàng)新理論的發(fā)展,方法和算法,對信息的加工、處理,理解,等等。該雜志的目標是編年史的重要出版物,在快速增長的數(shù)據(jù)表示和分析領域,以刺激相關跨學科領域的研究,并提供一個共同的聯(lián)系,在數(shù)學,物理,生命科學家,以及工程師。應用諧波分析和計算諧波分析涵蓋了最廣泛的意義上的主題,包括但不限于:一、信號和函數(shù)表示?連續(xù)和離散小波變換?小波幀?小波算法?局部時頻和時標基函數(shù)?多尺度、多層次的方法?refinable功能二、抽象高維對象的表示?擴散小波與幾何?對圖和樹進行諧波分析?稀疏數(shù)據(jù)表示?壓縮采樣?壓縮傳感?矩陣完成?隨機矩陣和投影?數(shù)據(jù)降維?高維積分三世應用領域?數(shù)據(jù)壓縮?信號和圖像處理?學習理論和算法?計算機輔助幾何設計?超大數(shù)據(jù)分析和理解?數(shù)據(jù)恢復和圖像繪制?數(shù)據(jù)挖掘?高光譜成像?新型傳感器和系統(tǒng)

APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS英文簡介

Applied and Computational Harmonic Analysis (ACHA) is an interdisciplinary journal that publishes high-quality papers in all areas of mathematical sciences related to the applied and computational aspects of harmonic analysis, with special emphasis on innovative theoretical development, methods, and algorithms, for information processing, manipulation, understanding, and so forth. The objectives of the journal are to chronicle the important publications in the rapidly growing field of data representation and analysis, to stimulate research in relevant interdisciplinary areas, and to provide a common link among mathematical, physical, and life scientists, as well as engineers. Applied and computational harmonic analysis covers, in the broadest sense, topics that include but not limited to:I Signal and Function Representations? continuous and discrete wavelet transform? wavelet frames? wavelet algorithms?local time-frequency and time-scale basis functions? multi-scale and multi-level methods? refinable functionsII Representation of Abstract and High-dimensional Objects ? diffusion wavelets and geometry? harmonic analysis on graphs and trees? sparse data representation? compressive sampling? compressed sensing? matrix completion? random matrices and projections? data dimensionality reduction? high-dimensional integrationIII Application Areas? data compression? signal and image processing? learning theory and algorithms? computer-aided geometric design ? extra large data analysis and understanding? data recovery and image inpainting? data mining? hyperspectral imaging? novel sensors and systems

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