EDBT 2026 Demo / reviewers in the wild / expert
Charles C. Kilgus
dblp:136/6888
· DBLP profile ↗
6ranked-venue papers
3as first author
0since 2021 · last 1997
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2 · 2 first-authorTheory of computation · 2 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
2 papers |
Coding theory · 100% | |
| Computer networks
2 papers |
Physical-layer communications · 83% Network measurement and analytics · 17% |
Topics — the 11 heaviest of 11, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › error-correcting codes
cyclic codes |
0.0 | 2 | 1972 | A class of cyclic unequal error protection codes (Corresp.) · IEEE Trans. Inf. Theory 1972 Cyclic codes with unequal error protection (Corresp.) · IEEE Trans. Inf. Theory 1971 |
Coding theory
error-correcting codes |
0.0 | 2 | 1972 | A class of cyclic unequal error protection codes (Corresp.) · IEEE Trans. Inf. Theory 1972 Cyclic codes with unequal error protection (Corresp.) · IEEE Trans. Inf. Theory 1971 |
Physical-layer communications
channel coding |
0.0 | 2 | 1973 | Root-Mean-Square Error in Encoded Digital Telemetry · IEEE Trans. Commun. 1972 Pseudonoise Code Acquisition Using Majority Logic Decoding · IEEE Trans. Commun. 1973 |
Physical-layer communications › channel coding › error control coding › decoding
majority-logic decoding |
0.0 | 1 | 1973 | Pseudonoise Code Acquisition Using Majority Logic Decoding · IEEE Trans. Commun. 1973 |
Physical-layer communications › spread spectrum › code acquisition
PN code acquisition |
0.0 | 1 | 1973 | Pseudonoise Code Acquisition Using Majority Logic Decoding · IEEE Trans. Commun. 1973 |
Physical-layer communications
spread spectrum |
0.0 | 1 | 1973 | Pseudonoise Code Acquisition Using Majority Logic Decoding · IEEE Trans. Commun. 1973 |
Network measurement and analytics
telemetry |
0.0 | 1 | 1972 | Root-Mean-Square Error in Encoded Digital Telemetry · IEEE Trans. Commun. 1972 |
Coding theory › error-correcting codes › decoding › majority-logic decoding
majority-logic decodable codes |
0.0 | 1 | 1972 | A class of cyclic unequal error protection codes (Corresp.) · IEEE Trans. Inf. Theory 1972 |
Coding theory › error-correcting codes
unequal error protection codes |
0.0 | 1 | 1972 | A class of cyclic unequal error protection codes (Corresp.) · IEEE Trans. Inf. Theory 1972 |
Coding theory › error-correcting codes
unequal error protection |
0.0 | 1 | 1971 | Cyclic codes with unequal error protection (Corresp.) · IEEE Trans. Inf. Theory 1971 |
Coding theory › error-correcting codes › block codes
linear code |
0.0 | 1 | 1971 | Cyclic codes with unequal error protection (Corresp.) · IEEE Trans. Inf. Theory 1971 |
Methods — techniques the papers use, named apart from their topics
zero-sampling-error lower bound · 0.0probability bound derivation · 0.0majority-logic decoding · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1997 | A fuzzy logic technique for correcting climatological ionospheric modelsabstractThis paper reports on a fuzzy logic correction technique for the IRI90 climatological ionospheric model that uses a sparse set of GPS total electron content (TEC) measurements to provide a significant model correction over the entire sub-solar equatorial bulge. Crisp inputs, represented by a sparse set of GPS measurements of ionospheric TEC, are ingested into the fuzzy correction model which is composed of a set of fuzzy membership functions and a knowledge base (fuzzy rules). The fuzzy logic estimation is an iterative procedure that begins with the uncorrected model as the zero order prediction of the shape of the subsolar equatorial bulge. The measured data (inputs) are fuzzified to account for errors in the GPS measurements of TEC, and then are mapped onto fuzzy input-membership functions. The knowledge base is then accessed, firing the appropriate rules, to produce a fuzzy output estimate of the correction. This fuzzy estimate is then defuzzified to provide a crisp output correction that modifies the shape of the zero order prediction bulge to better fit the GPS data and to produce a first order prediction. The procedure is repeated until termination criteria are satisfied. The goal of the process is to accurately reproduce the characteristic signature of the ionospheric TEC along a satellite subtrack across the sub-solar equatorial bulge. The fuzzy logic model can make large scale alterations to the model prediction without requiring an extensive measurement data set and without inducing spikes in the local vicinity of the ingested data points. In particular, the IRI90 climatological model estimates of the ionospheric TEC were adjusted using two concurrent TEC measurements at locations approximately 800 km apart along the satellite ground track. For this first test, two simulated GPS measurements were derived from TOPEX dual-frequency TEC data. The results were compared with the TOPEX TEC measurements for four ground tracks in the Pacific across the subsolar equatorial bulge. Initial results showed a model improvement to within -0.32 TECU averaged over four entire passes (/spl plusmn/66/spl deg/ latitude) when compared with the TOPEX "ground truth" measured TEC along track profiles. (1 TECU equals 10/sup 16/ electrons/m/sup 2/.) The mean error over the equatorial portion of the passes (/spl plusmn/20/spl deg/ latitude) was -4.65 TECU. The fuzzy correction model was run for 18 iterations, approximately full convergence. The averaging over sunlit passes provides an upper bound on the error since the spatial and temporal sampling allowed by the equatorial application include night time passes with low TEC. The residual error is dominated by the failure to match the structure of the TEC peaks north and south of the geomagnetic equator. Incorporating measured global averaged ionospheric geomagnetic index and a local solar zenith angle as inputs to the fuzzy logic may allow this error to be reduced. Fine tuning of the fuzzy logic model rules and full development of the multi-GPS station ingestion scheme can now proceed given that this first test shows that potentially the fuzzy logic correction is able to produce a correction that could satisfy the equatorial basin-scale measurement needs for GFO. Judith A. Giannini, Charles C. Kilgus |
IEEE Trans. Geosci. Remote. Sens. | 2 |
| 1993 | Prelaunch performance of the NASA altimeter for the TOPEX/Poseidon projectabstractThe TOPEX/Poseidon radar altimeter satellite applies advances in remote sensing instrumentation to reduce long wavelength measurement errors to dramatically lower levels. The TOPEX altimeter measures the range to the ocean surface with 2-cm precision and accuracy through the use of both Ku- and C-band radars, a high pulse repetition frequency, an agile tracker, and absolute internal height calibration. Dual pulse bandwidths for both frequencies make it possible to quickly acquire the surface and begin tracking after crossing the land/ocean boundary. The altimeter requirements and the elements of the altimeter design that have resulted in meeting these requirements are presented. Prelaunch test data, based on the use of a radar altimeter system evaluator to simulate the backscatter from the ocean surface, are presented to demonstrate that the TOPEX altimeter will meet these requirements and provide the data necessary to the understanding of basin scale mean circulation.> Paul C. Marth, J. Robert Jensen, Charles C. Kilgus, James A. Perschy, John L. MacArthur, David W. Hancock, George S. Hayne, Craig L. Purdy, Laurence C. Rossi, Chester J. Koblinsky |
IEEE Trans. Geosci. Remote. Sens. | 3 |
| 1973 | Pseudonoise Code Acquisition Using Majority Logic DecodingabstractThis paper considers the use of majority logic decoding as a pseudonoise code acquisition technique. A bound on the probability of code acquisition is derived and it is shown that the probability of acquiring an 8191 code in one attempt can be made nearly one at -10-dB SNR. Charles C. Kilgus |
IEEE Trans. Commun. | 1 |
| 1972 | Root-Mean-Square Error in Encoded Digital TelemetryabstractThis paper studies the effectiveness of certain group codes in reducing the root-mean-square (rms) error in a digital telemetry link. The zero-sampling-error lower bound on the total error is derived for the case when majority-logic-decodable group codes are used in the channel. Calculated data are presented for several such codes including two new cyclic unequal-error-protection codes. Charles C. Kilgus, Willis C. Gore |
IEEE Trans. Commun. | 1 |
| 1972 | A class of cyclic unequal error protection codes (Corresp.)abstractThis correspondence presents a new class of cyclic majority-logic decodable codes. The codes provide unequal error protection for the information digits, i.e., some decoded digits are guaranteed to be correct despitet_1or fewer channel errors even though the minimum distance of the code guarantees protection from onlyt_0errors andt_1 > t_0. Charles C. Kilgus, Willis C. Gore |
IEEE Trans. Inf. Theory | 1 |
| 1971 | Cyclic codes with unequal error protection (Corresp.)abstractThis paper shows that, although systematic cyclic codes have equal error protection for all information digits, there exist non-systematic cyclic codes that can provide unequal error protection for the information digits; that is, at least one information digit is protected for a number of errors that is larger than the number guaranteed by the minimum distance of the code. Willis C. Gore, Charles C. Kilgus |
IEEE Trans. Inf. Theory | 2 |