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APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

應用和計算諧波分析

期刊周期:Bimonthly
研究方向:數學
影響因子:2.964
通訊地址:ACADEMIC PRESS INC ELSEVIER SCIENCE, 525 B ST, STE 1900, SAN DIEGO, USA, CA, 92101-4495
官網:http://www.journals.elsevier.com/applied-and-computational-harmonic-analysis/
投稿地址:http://ees.elsevier.com/acha/default.asp?acw=6012
審稿速度:較慢,6-12周

  中文簡介

應用和計算諧波分析(據)是一個跨學科期刊發表高質量的論文在數學科學的所有領域相關諧波分析的應用和計算方面,特別強調創新理論的發展,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,在快速增長的數據表示和分析領域,以刺激相關跨學科領域的研究,并提供一個共同的聯系,在數學,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、信號和函數表示?連續和離散小波變換?小波幀?小波算法?局部時頻和時標基函數?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?稀疏數據表示?壓縮采樣?壓縮傳感?矩陣完成?隨機矩陣和投影?數據降維?高維積分三世應用領域?數據壓縮?信號和圖像處理?學習理論和算法?計算機輔助幾何設計?超大數據分析和理解?數據恢復和圖像繪制?數據挖掘?高光譜成像?新型傳感器和系統

  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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