Name
Abstract | ||
|---|---|---|
The development and comparison of a class of nonparametric probability density function modeling algorithms is presented. Each algorithm Iteratively estimates a model of the sampled density function based upon a description of a set of equiprobable regions over the range of the variable of interest. Minimization of computational complexity and memory capacity while maintaining convergence and stability are the principal considerations. Variations of the algorithms are compared as to rate of convergence and limit cycle stability relative to ease of implementation. Results including comparative curves are presented. |
Year | DOI | Venue |
|---|---|---|
1972 | 10.1109/TSMC.1972.4309136 | IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS |
Keywords | Field | DocType |
stability,shape,limit cycle,computational complexity,convergence,entropy,density functional theory,probability density function,rate of convergence | Convergence (routing),Asymptotic computational complexity,Mathematical optimization,Computer science,Algorithm,Probabilistic analysis of algorithms,Limit cycle,Nonparametric statistics,Rate of convergence,Probability density function,Computational complexity theory | Journal |
Volume | Issue | ISSN |
SMC2 | 3 | 0018-9472 |
Citations | PageRank | References |
2 | 0.72 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kenneth W. Drake | 1 | 2 | 0.72 |
| Lester A. Gerhardt | 2 | 78 | 14.54 |