FIELD: computer engineering.
SUBSTANCE: technical result is achieved due to a robust stochastic filter comprising an adder, a subtractor, an integrator, a multiplier and four functional conversion units.
EFFECT: high accuracy of filtering nonlinear dynamic processes in the presence of noise of the observed object and measurement noise with unknown probability distributions.
1 cl, 1 dwg
| Title | Year | Author | Number |
|---|---|---|---|
| ROBUST STOCHASTIC FILTER | 2021 |
|
RU2755677C1 |
| ROBUST DISCRETE STOCHASTIC FILTER | 2023 |
|
RU2804256C1 |
| METHOD FOR POSITIONING MOVING VEHICLE | 2023 |
|
RU2811665C1 |
| KALMAN FILTER | 0 |
|
SU1385265A1 |
| ADAPTIVE FILTER FOR ESTIMATING TRANSIENT PROCESSES | 1993 |
|
RU2110883C1 |
| SUBOPTIMUM FILTER FOR ASSESSING RANDOM PROCESS PARAMETER | 0 |
|
SU1619307A1 |
| ADAPTIVE FILTERING DEVICE | 0 |
|
SU1436271A1 |
| STOCHASTIC FILTER | 0 |
|
SU1675905A1 |
| ADAPTIVE TELEMETRIC MEASUREMENT FILTER FOR OPERATION UNDER CONDITIONS OF A PRIORI UNCERTAINTY | 2019 |
|
RU2736282C1 |
| NON-LINEAR PROBABILITY CONVERTER | 0 |
|
SU610119A1 |
