APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

所属栏目:SCI期刊 热度:452

APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

期刊周期:Bimonthly
研究方向:数学
影响因子:2.964
通讯地址:ACADEMIC PRESS INC ELSEVIER SCIENCE, 525 B ST, STE 1900, SAN DIEGO, USA, CA, 92101-4495
官网:http://www.journals.elsevier.com/applied-and-computational-harmonic-analysis/
投稿地址:http://ees.elsevier.com/acha/default.asp?acw=6012
审稿速度:较慢,6-12周

  中文简介

应用和计算谐波分析(据)是一个跨学科期刊发表高质量的论文在数学科学的所有领域相关谐波分析的应用和计算方面,特别强调创新理论的发展,方法和算法,对信息的加工、处理,理解,等等。该杂志的目标是编年史的重要出版物,在快速增长的数据表示和分析领域,以刺激相关跨学科领域的研究,并提供一个共同的联系,在数学,物理,生命科学家,以及工程师。应用谐波分析和计算谐波分析涵盖了最广泛的意义上的主题,包括但不限于:一、信号和函数表示?连续和离散小波变换?小波帧?小波算法?局部时频和时标基函数?多尺度、多层次的方法?refinable功能二、抽象高维对象的表示?扩散小波与几何?对图和树进行谐波分析?稀疏数据表示?压缩采样?压缩传感?矩阵完成?随机矩阵和投影?数据降维?高维积分三世应用领域?数据压缩?信号和图像处理?学习理论和算法?计算机辅助几何设计?超大数据分析和理解?数据恢复和图像绘制?数据挖掘?高光谱成像?新型传感器和系统

  英文简介

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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