def grad_Q0(Gamma0, B7, q, prior_Q0):
eig_Q_sqrt, inv_Q = _util_obj_grad_AQ(Gamma0)
grad_Gamma0 = reduce(np.dot, [inv_Q, np.float(q)*np.eye(Gamma0.shape[0])- B7.dot(inv_Q), Gamma0])
if prior_Q0 is not None:
grad_Gamma0 += grad_prior_Q(Gamma0, prior_Q0)
grad_Gamma0 = np.tril(grad_Gamma0)
return grad_Gamma0
# gradient descent
ROI_Kalman_smoothing.py 文件源码
python
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