| 1. |
|
|
| 2. |
- Dzhafarov, Ehtibar N., et al.
(författare)
-
Mental architectures with selectively influenced but stochastically interdependent components
- 2004
-
Ingår i: Journal of mathematical psychology (Print). - : Elsevier BV. - 0022-2496 .- 1096-0880. ; 48:1, s. 51-64
-
Tidskriftsartikel (refereegranskat)abstract
- The way external factors influence distribution functions for the overall time required to perform a mental task (such as responding to a stimulus, or solving a problem) may be informative as to the underlying mental architecture, the hypothetical network of interconnected processes some of which are selectively influenced by some of the external factors. Under the assumption that all processes contributing to the overall performance time are stochastically independent, several basic results have been previously established. These results relate patterns of response time distribution functions produced by manipulating external factors to such questions as whether the hypothetical constituent processes in the mental architecture enter AND gates or OR gates, and whether pairs of processes are sequential or concurrent. The present study shows that all these results are also valid for stochastically interdependent component times, provided the selective dependence of these components upon external factors is understood within the framework of a recently proposed theory of selective influence. According to this theory each component is representable as a function of three arguments: the factor set selectively influencing it, a component-specific source of randomness, and a source of randomness shared by all the components.
|
|
| 3. |
|
|
| 4. |
|
|
| 5. |
- Kim, Sung-Phil, et al.
(författare)
-
Divide-and-conquer approach for brain machine interfaces: nonlinear mixture of competitive linear models.
- 2003
-
Ingår i: Neural networks : the official journal of the International Neural Network Society. - 0893-6080. ; 16:5-6, s. 865-71
-
Tidskriftsartikel (refereegranskat)abstract
- This paper proposes a divide-and-conquer strategy for designing brain machine interfaces. A nonlinear combination of competitively trained local linear models (experts) is used to identify the mapping from neuronal activity in cortical areas associated with arm movement to the hand position of a primate. The proposed architecture and the training algorithm are described in detail and numerical performance comparisons with alternative linear and nonlinear modeling approaches, including time-delay neural networks and recursive multilayer perceptrons, are presented. This new strategy allows training the local linear models using normalized LMS and using a relatively smaller nonlinear network to efficiently combine the predictions of the linear experts. This leads to savings in computational requirements, while the performance is still similar to a large fully nonlinear network.
|
|
| 6. |
- Yu, Sung W., et al.
(författare)
-
Anionic and cationic photofragmentation of core-excited N2O
- 2003
-
Ingår i: J. Phys. B: At. Mol. Opt. Phys. - 0953-4075. ; 36, s. 1255-1261
-
Tidskriftsartikel (refereegranskat)abstract
- We have measured all detectable cationic and anionic fragments in singlechannel mode from N2O as a function of photon energy in the vicinity of the nitrogen 1s core-level threshold. Due to the high degree of localization of the core electrons, the two excitations Nt1s → 3π∗ and Nc1s → 3π∗ show high levels of site-selective behaviour. The observed partial ion yield for the sole anionic fragment,O−, in conjunctionwith the partial cation yields,confirms our previous demonstration of anion-yield spectroscopy as a unique tool to identify core-level shape resonances.
|
|
