Muhammad Z. Ikram

32 total papers · 698 total citations
25 papers, 457 citations indexed

About

Muhammad Z. Ikram is a scholar working on Signal Processing, Computational Mechanics and Electrical and Electronic Engineering. According to data from OpenAlex, Muhammad Z. Ikram has authored 25 papers receiving a total of 457 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Signal Processing, 10 papers in Computational Mechanics and 9 papers in Electrical and Electronic Engineering. Recurrent topics in Muhammad Z. Ikram's work include Blind Source Separation Techniques (12 papers), Advanced Adaptive Filtering Techniques (10 papers) and Speech and Audio Processing (9 papers). Muhammad Z. Ikram is often cited by papers focused on Blind Source Separation Techniques (12 papers), Advanced Adaptive Filtering Techniques (10 papers) and Speech and Audio Processing (9 papers). Muhammad Z. Ikram collaborates with scholars based in United States, Australia and Pakistan. Muhammad Z. Ikram's co-authors include Dennis R. Morgan, Karim Abed‐Meraim, Yingbo Hua, G. Tong Zhou, Adeel Ahmad, Murtaza Ali, Dan Wang, Mazhar Sher, G. Tong Zhou and Adel Belouchrani and has published in prestigious journals such as IEEE Transactions on Signal Processing, Computers and Electronics in Agriculture and Electronics Letters.

In The Last Decade

Muhammad Z. Ikram

24 papers receiving 423 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Muhammad Z. Ikram	292	180	87	87	66	25	457
Dominique Pastor	193 0.7×	127 0.7×	34 0.4×	63 0.7×	115 1.7×	52	460
Koby Todros	245 0.8×	102 0.6×	53 0.6×	39 0.4×	25 0.4×	44	430
V.U. Reddy	376 1.3×	140 0.8×	114 1.3×	81 0.9×	18 0.3×	35	463
S.V. Schell	425 1.5×	191 1.1×	69 0.8×	136 1.6×	13 0.2×	32	527
Srdjan Stanković	147 0.5×	93 0.5×	46 0.5×	79 0.9×	145 2.2×	23	475
S. Attallah	278 1.0×	204 1.1×	55 0.6×	246 2.8×	56 0.8×	63	517
H Mathis	244 0.8×	102 0.6×	112 1.3×	191 2.2×	30 0.5×	41	477
Veselin N. Ivanović	216 0.7×	125 0.7×	41 0.5×	109 1.3×	190 2.9×	48	445
G. Bienvenu	345 1.2×	90 0.5×	119 1.4×	75 0.9×	27 0.4×	20	454
K. Lebart	235 0.8×	153 0.8×	38 0.4×	36 0.4×	113 1.7×	20	464

Countries citing papers authored by Muhammad Z. Ikram

Since Specialization

Citations

This map shows the geographic impact of Muhammad Z. Ikram's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Muhammad Z. Ikram with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Z. Ikram more than expected).

Fields of papers citing papers by Muhammad Z. Ikram

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Z. Ikram. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Muhammad Z. Ikram. The network helps show where Muhammad Z. Ikram may publish in the future.

Co-authorship network of co-authors of Muhammad Z. Ikram

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Z. Ikram. A scholar is included among the top collaborators of Muhammad Z. Ikram based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Muhammad Z. Ikram. Muhammad Z. Ikram is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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