The construction of visual objects does not depend exclusively on sensory cues but is shaped also by experience-dependent expectations.
Choi et al.43 demonstrated that context-dependent expectations of either a daily meal or a palatable food reward increased c-Fos expression in orexin neurons in the Pef, and central administration of orexin A increased the motivation to obtain the food reward.
The MR images are used to obtain an initial attenuation map and to derive voxel-dependent expectations on the attenuation coefficients.
As a result, students' prior experiences in the national examination (PSLE) and most of the scfhool exams in Singapore taken by all primary students may have rendered the students "grades and scores-dependent" expectations.
Then the time-dependent expectation value of any observable is (6).
On the other hand, the model-dependent expectation involves a sum over all (2^K) elements of u as well as the (2^T) elements of h.
Therefore, exact computation of the data-dependent expectation is intractable because its complexity is exponential in the number of visible and hidden layer nodes.
Once sufficient number of samples are obtained with Gibbs sampling, the Monte Carlo approach can be used to approximate the model-dependent expectation specified in Eq. (14).
Similarly, the second term is the expectation of the gradient of the energy function with respect to (p({mathbf{u}}, {mathbf{h}} )) and is known as model-dependent expectation.
The first term of Eq. (13) is the expectation of the gradient of the energy function with respect to (p({mathbf{h}} mid {mathbf{u}} _s)) and is termed as data-dependent expectation.
To avoid this computational burden, the data-dependent expectation can be approximated by generating a finite number of samples from the joint distribution (p({mathbf{u}},{mathbf{h}} )) using the Markov Chain Monte Carlo (MCMC) [24] technique.
