| Jordan, M. I. (1992). Constrained supervised learning. J. of Mathematical Psychology, 36:396--425. Jordan, M. I. (1996). Computational aspects of motor control and motor learning. In Heuer, H. and Keele, S., editors, Handbook of Perception and Action: Motor Skills. Academic Press, New York. |
....and the past output rather than the past input. The idea stems from speech recognition, where the phenomenon of a long influence of past outputs is observed. This quite plausible when we realize that the pronounciation of a certain vowel can be influenced by the preceeding four or five consonants (Jordan (1992), Jordan (1986) So the idea was to feed back the output rather than the nonlinear transformation of the state. As can be seen from a straight forward calculation the Jordan network can also be written as y t = H oe[CA t x 0 t X j=1 CA j;1 By t;j Du t ] 3) Results analogous to those ....
Jordan, M. I. (1992). Constrained supervised learning. J. of Mathematical Psychology 36, 396--425.
....(t) T q i (t) 28) where q i (t) is a d dimensional vector whose jth element is q i j (t) Figure 1 shows how this probability model is formally equivalent to a special type of highly constrained connectionist network. For expository reasons, consider a Jordan style connectionist network (Jordan, 1992) with an exponentially decaying memory. For networks of this type, the 8 function in (24) can be recursively defined as: y i (t) 8(x i (t 0 1) y i (t 0 1) x i (t 0 1) y i (t 0 1) 29) where y i (1) is a vector of zeroes. The ith activation pattern over the input units at time ....
Jordan, M. I. (1992). Constrained supervised learning. Journal of Mathematical Psychology, 36, 396--425.
....possible articulatory states, but each of those articulatory states maps only to silence. From the perspective of control theory, the mapping from proximal domain (articulation) to the distal domain (acoustics) is termed the forward mapping, whereas the reverse is termed the inverse mapping (see Jordan, 1992, 1996) When the inverse mapping is many to one, as in this case, it constitutes a motor equivalence problem. This problem must be solved if the link between articulation and acoustics is to support the acquisition of speech production. Our solution to the motor equivalence problem is based on ....
Jordan, M. I. (1992). Constrained supervised learning. Journal of Mathematical Psychology, 36, 396--425.
No context found.
Jordan, M. I. (1992). Constrained supervised learning. J. of Mathematical Psychology, 36:396--425. Jordan, M. I. (1996). Computational aspects of motor control and motor learning. In Heuer, H. and Keele, S., editors, Handbook of Perception and Action: Motor Skills. Academic Press, New York.
.... estimates for such systems under certain conditions (Goodwin Sin, 1984) For nonlinear systems, however, a di#culty arises that is related to the general degrees of freedom problem in motor control (Bernstein, 1967) The problem is due to a particular form of redundancy in nonlinear systems (Jordan, 1992). In such systems, the optimal parameter estimates (i.e. those that minimize the cost function in Equation 40) in fact yield an incorrect controller. 41 Plant D .5 .4 u n [ y n [ 2 D D v 1 v u n [ 1] Figure 19: An example of the direct inverse modeling ....
Jordan, M. I. (1992). Constrained supervised learning. Journal of Mathematical Psychology, 36, 396-425.
No context found.
M. I. Jordan, "Constrained supervised learning," J. Math. Psych., vol. 36, pp. 396--425, 1992.
No context found.
M. I. Jordan, "Constrained Supervised Learning," Journal of Mathematical Psychology, Vol. 36, pp. 396-425, 1992.
No context found.
M.I. Jordan, "Constrained Supervised Learning", Journal of Mathematical Psychologie , Vol 36, pp. 396-425, 1992
No context found.
M. Jordan, "Constrained Supervised Learning," Journal of Mathematical Psychology , Vol. 36, pp. 396-- 425, 1992.
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