Muhammad Z. Ikram

698 citations
25 papers · 458 indexed · h-index 12
Topics
Blind Source Separation Techniques (12 papers)Advanced Adaptive Filtering Techniques (10 papers)Speech and Audio Processing (9 papers)

In The Last Decade

Muhammad Z. Ikram

24 papers receiving 424 citations

Peers

Muhammad Z. Ikram
Comparison fields: 5 of 45
  • Signal Processing 292
  • Computational Mechanics 180
  • Aerospace Engineering 88
  • Electrical and Electronic Engineering 88
  • Computer Vision and Pattern Recognition 66
Replace Sze Fong Yau with:
Sze Fong Yau Hong Kong
S. Attallah Singapore
Veselin N. Ivanović Montenegro
H Mathis Switzerland
José L. Paredes Venezuela
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Fu‐Kun Chen Taiwan
X.-G. Xia United States
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Muhammad Z. Ikram relative to Sze Fong Yau Hong Kong Sze Fong Yau's profile →
Citations per field
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Citations per year

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

20 of 20 papers shown
#WorkIndexed citations
1 18
2 13
3 22
4 7
5 9
6 1
7 14
8 2
9 4
10
An enhanced closed-loop MIMO design for OFDM/OFDMA-PHY
6
11 62
12 7
13 1
14 3
15 88
16 3
17 5
18 38
19 45
20 3

About Muhammad Z. Ikram

Muhammad Z. Ikram is a scholar working on Signal Processing, Computational Mechanics and Aerospace Engineering, having authored 25 papers that have together received 458 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (12 papers), Advanced Adaptive Filtering Techniques (10 papers) and Speech and Audio Processing (9 papers). The work is most often cited by research in Signal Processing (292 citations), Computational Mechanics (180 citations) and Aerospace Engineering (88 citations). Muhammad Z. Ikram has collaborated with scholars based in United States, Australia and Algeria. Frequent co-authors include Dennis R. Morgan, Karim Abed‐Meraim, Yingbo Hua, G. Tong Zhou, Adeel Ahmad, Murtaza Ali, Dan Wang, Ashfaq Ahmad, Mazhar Sher and Young Chang. Their work appears in journals such as IEEE Transactions on Signal Processing, Computers and Electronics in Agriculture and Electronics Letters.

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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