Description: To estimate the input-output mapping with inputs x
％ and outputs y generated by the following nonlinear,
％ nonstationary state space model:
％ x(t+1) = 0.5x(t) + [25x(t)]/[(1+x(t))^(2)]
％ + 8cos(1.2t) + process noise
％ y(t) = x(t)^(2) / 20 + 6 squareWave(0.05(t-1)) + 3
％ + time varying measurement noise
％ using a multi-layer perceptron (MLP) and both the EKF and
％ the hybrid importance-samping resampling (SIR) algorithm. -To estimate the input-output mapping with inputs x and outputs y generated by the following nonlinear, nonstationary state space model: x (t+ 1) = 0.5x (t)+ [25x (t )]/[( 1+ x (t)) ^ (2)]+ 8cos (1.2t)+ process noise y (t) = x (t) ^ (2)/20+ 6 squareWave (0.05 (t-1 ))+ 3+ time varying measurement noise using a multi-layer perceptron (MLP) and both the EKF and the hybrid importance-samping resampling (SIR) algorithm. Platform: |
Size: 40960 |
Author:Lin |
Hits:
Description: MLP graph input-output mapping with inputs x and outputs y generated by the following nonlinear, Platform: |
Size: 1024 |
Author:cnabro |
Hits:
Description: 使用matlab不依靠库函数编写的BP网络，多层感知器，以及利用BP网络做的函数逼近。-Use matlab not rely on library functions of BP network to write, multi-layer perceptron, and the use of BP network do function approximation.
Platform: |
Size: 8192 |
Author:刘颖 |
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Description: Major features
BNT supports many types of conditional probability distributions (nodes), and it is easy to add more.
Tabular (multinomial)
Gaussian
Softmax (logistic/ sigmoid)
Multi-layer perceptron (neural network)
Noisy-or
Deterministic
Platform: |
Size: 12275013 |
Author:SunStacy |
Hits:
Search - multi layer perceptron matlab