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- Psychology (8)
- General recognition theory (2)
- Capacity (1)
- Capacity coefficient (1)
- Coactive (1)
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- Configural information (1)
- Configuration (1)
- Dots (1)
- Efficiency (1)
- Emergent features (1)
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- Human information processing (1)
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- Response time (1)
- Response times (1)
- Simple Emergent Feature Processing (1)
- Statistics (1)
- Stochastic dynamics (1)
- Survivor Interaction Contrast (1)
- Survivor interaction contrast (1)
- Visual word perception (1)
- Workload capacity (1)
- Publication
Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Configuration As A Source Of Information, Joseph W. Houpt, Robert D. Hawkins, Ami Eidels, James T. Townsend, Michael J. Wenger
Configuration As A Source Of Information, Joseph W. Houpt, Robert D. Hawkins, Ami Eidels, James T. Townsend, Michael J. Wenger
Joseph W. Houpt
No abstract provided.
Fundamental Properties Of Simple Emergent Feature Processing, Robert D. Hawkins, Joseph W. Houpt, Ami Eidels, James T. Townsend, Michael J. Wenger
Fundamental Properties Of Simple Emergent Feature Processing, Robert D. Hawkins, Joseph W. Houpt, Ami Eidels, James T. Townsend, Michael J. Wenger
Joseph W. Houpt
No abstract provided.
From Deep Space 9 To The Gamma Quadrant!, James T. Townsend, Joseph W. Houpt
From Deep Space 9 To The Gamma Quadrant!, James T. Townsend, Joseph W. Houpt
Joseph W. Houpt
No abstract provided.
A Statistical Test For The Capacity Coefficient, Joseph W. Houpt, James T. Townsend
A Statistical Test For The Capacity Coefficient, Joseph W. Houpt, James T. Townsend
Joseph W. Houpt
No abstract provided.
General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, Joseph W. Houpt, James T. Townsend, Noah H. Silbert
General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, Joseph W. Houpt, James T. Townsend, Noah H. Silbert
Joseph W. Houpt
No abstract provided.
An Extension Of Sic Predictions To The Wiener Coactive Model, Joseph W. Houpt, James T. Townsend
An Extension Of Sic Predictions To The Wiener Coactive Model, Joseph W. Houpt, James T. Townsend
Joseph W. Houpt
The survivor interaction contrasts (SIC) is a powerful measure for distinguishing among candidate models of human information processing. One class of models to which SIC analysis can apply are the coactive, or channel summation, models of human information processing. In general, parametric forms of coactive models assume that responses are made based on the first passage time across a fixed threshold of a sum of stochastic processes. Previous work has shown that the SIC for a coactive model based on the sum of Poisson processes has a distinctive down--up--down form, with an early negative region that is smaller than the …
A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend
A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend
Joseph W. Houpt
No abstract provided.
Multiple Solutions For An Elliptic Problem Related To Vortex Pairs, Yi Li, Shuangjie Peng
Multiple Solutions For An Elliptic Problem Related To Vortex Pairs, Yi Li, Shuangjie Peng
Yi Li
Let Ω be a bounded domain in RN (N⩾2), φ a harmonic function in Ω¯. In this paper we study the existence of solutions to the following problem arising in the study of vortex pairs(Pλ){−Δu=λ(u−φ)+p−1,x∈Ω,u=0,x∈∂Ω. The set Ωp={x∈Ω,u(x)>φ} is called “vortex core”. Existence of solutions whose “vortex core” consists of one component and asymptotic behavior of “vortex core” were studied by many authors for large λ recently. Under the condition that φ has k strictly local minimum points on the boundary ∂Ω, we obtain in this paper that for λ large enough, (Pλ) has a solution with “vortex core” …
Nice Guys Finish Fast And Bad Guys Finish Last: Facilitatory Vs. Inhibitory Interaction In Parallel Systems, Ami Eidels, Joseph W. Houpt, Nicholas Altieri, Lei Pei, James T. Townsend
Nice Guys Finish Fast And Bad Guys Finish Last: Facilitatory Vs. Inhibitory Interaction In Parallel Systems, Ami Eidels, Joseph W. Houpt, Nicholas Altieri, Lei Pei, James T. Townsend
Joseph W. Houpt
Systems Factorial Technology is a powerful framework for investigating the fundamental properties of human information processing such as architecture (i.e., serial or parallel processing) and capacity (how processing efficiency is affected by increased workload). The Survivor Interaction Contrast (SIC) and the Capacity Coefficient are effective measures in determining these underlying properties, based on response-time data. Each of the different architectures, under the assumption of independent processing, predicts a specific form of the SIC along with some range of capacity. In this study, we explored SIC predictions of discrete-state (Markov process) and continuous-state (Linear Dynamic) models that allow for certain types …