Name
Abstract | ||
|---|---|---|
This paper considers the problem of estimating the cumulative distribution function and probability density function of a random variable using data quantized by uniform and non-uniform quantizers. A simple estimator is proposed based on the empirical distribution function that also takes the values of the quantizer transition levels into account. The properties of this estimator are discussed and... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TIM.2016.2540865 | IEEE Transactions on Instrumentation and Measurement |
Keywords | Field | DocType |
Data acquisition,Probability density function,Estimation,Instruments,Distribution functions,Quantization (signal),Noise measurement | Random variable,Empirical distribution function,Characteristic function (probability theory),Electronic engineering,Cumulative distribution function,Quantization (signal processing),Probability density function,Inverse transform sampling,Mathematics,Estimator | Journal |
Volume | Issue | ISSN |
65 | 7 | 0018-9456 |
Citations | PageRank | References |
3 | 0.43 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| P. Carbone | 1 | 192 | 45.32 |
| Johan Schoukens | 2 | 376 | 58.12 |
| István Kollár | 3 | 57 | 10.07 |
| Antonio Moschitta | 4 | 236 | 35.04 |