Name
Title | ||
|---|---|---|
Gradient Of Error Probability Of M-Ary Hypothesis Testing Problems Under Multivariate Gaussian Noise |
Abstract | ||
|---|---|---|
This letter considers an M-ary hypothesis testing problem on an n-dimensional random vector perturbed by the addition of Gaussian noise. A novel expression for the gradient of the error probability, with respect to the covariance matrix of the noise, is derived and shown to be a function of the cross-covariance matrix between the noise matrix (i.e., the matrix obtained by multiplying the noise vector by its transpose) and Bernoulli random variables associated with the correctness event. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/LSP.2020.3031487 | IEEE SIGNAL PROCESSING LETTERS |
Keywords | DocType | Volume |
Error probability, hypothesis testing, gradient, multivariate Gaussian noise | Journal | 27 |
ISSN | Citations | PageRank |
1070-9908 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minoh Jeong | 1 | 0 | 0.34 |
| Alex Dytso | 2 | 45 | 20.03 |
| Martina Cardone | 3 | 47 | 18.36 |