J. Markel

6.2k citations
45 papers · 4.5k indexed · 1 hit paper · h-index 20

J. Markel

40 papers receiving 3.8k citations

Hit Papers

Linear Prediction of Speech1.6k197620261992200950010001.5k

Peers

J. Markel
Comparison fields: 5 of 122
  • Signal Processing 3.1k
  • Computer Vision and Pattern Recognition 1.6k
  • Artificial Intelligence 1.8k
  • Computational Mechanics 920
  • Experimental and Cognitive Psychology 494
Replace Bishnu S. Atal with:
Bishnu S. Atal United States
B. Yegnanarayana India
Julius O. Smith United States
James L. Flanagan United States
Ben Gold United States
J.R. Deller United States
M.H. Ackroyd United Kingdom
Fumitada Itakura Japan
W. Bastiaan Kleijn Sweden
Kiyohiro Shikano Japan
J. Markel relative to Bishnu S. Atal United States Bishnu S. Atal's profile →
Citations per field
00.5×1.5×
Bishnu S. Atal · 1×
Citations per year

Countries citing papers authored by J. Markel

Since Specialization
Citations

This map shows the geographic impact of J. Markel'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 J. Markel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Markel more than expected).

Fields of papers citing papers by J. Markel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. Markel. 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 J. Markel. The network helps show where J. Markel may publish in the future.

Co-authorship network

The 12 scholars most cited alongside J. Markel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with J. Markel Line = papers co-authored together J. Markel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20051
2 20050
3 20050
4 20051
5 1980411
6 19771
7 197761
8 197734
9 19764
10
Linear Prediction of Speechbreakdown →
19761627
11 19761
12 19754
13 197536
14 197497
15 197417
16 19740
17 197456
18 1973227
19 1973112
20 197313

About J. Markel

J. Markel is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Computational Mechanics, Artificial Intelligence and Experimental and Cognitive Psychology, having authored 45 papers that have together received 4.5k indexed citations. Recurring topics across this work include Speech and Audio Processing (28 papers), Speech Recognition and Synthesis (14 papers), Advanced Data Compression Techniques (13 papers), Digital Filter Design and Implementation (11 papers), Advanced Adaptive Filtering Techniques (10 papers), Image and Signal Denoising Methods (6 papers), Voice and Speech Disorders (6 papers) and Phonetics and Phonology Research (5 papers). The work is most often cited by research in Signal Processing (3.1k citations), Computer Vision and Pattern Recognition (1.6k citations), Artificial Intelligence (1.8k citations), Computational Mechanics (920 citations) and Experimental and Cognitive Psychology (494 citations). J. Markel has collaborated with scholars based in United States and Mexico. Frequent co-authors include Alfred Gray, Augustine H. Gray, Robert M. Gray, A. Buzo, David Y. Wong, Beatrice T. Oshika, S. Davis, Yasuo Koike, Robert D. Arnott and Steven J. Davis. Their work appears in journals such as The Journal of the Acoustical Society of America, Annals of Otology Rhinology & Laryngology, IEEE Transactions on Acoustics Speech and Signal Processing, UA Campus Repository (The University of Arizona) and IEEE Transactions on Audio and Electroacoustics.

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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