Parallel distributed processing models

McClelland JL and Rumelhart DE, The PDP Research Group 1986 Parallel Distributed Processing, Explorations in the Microstructure of Cognition, Volume 2 Psychological and Biological Models. The MIT Press, Cambridge, Massachusetts. 

McClelland, J. L. (1986). The programmable blackboard model of reading. In J. McClelland, D. E. Rumelhart, and the PDP Research Group (Eds.), Parallel distributed processing Explorations in the microstructures of cognition (Vol. 2, pp. 122-169). Cambridge MIT Press. 

The resulting models are referred to by various names, including neural networks, neurocomputers, Parallel Distributed Processing (PDP) models, neuromorphic systems, layered self-adaptive networks, and connectionist models. Here, we use the name neural networks, or neural nets for short. We use these networks as vehicles for adaptively developing the coefficients of decision function via successive presentations of training sets of patterns. 

McClelland J. L., Explorations in parallel distributed processing a handbook of models, programs and exercises, 2 edition, 2011, Stanford University, CA. 

Surface roughness is also expected to result in depression of the capacitance semi-circle. This phenomenon, which is indeed apparent in both Figures 1 and 2, is, however, unrelated to surface area. Rather, it is attributable to surface heterogeneity, i.e. the surface is characterized by a distribution of properties. Macdonald (16) recently reviewed techniques for representing distributed processes. A transmission line model containing an array of parallel R/C units with a distribution of values is physically attractive, but not practical. An alternative solution is introduction of an element which by its very nature is distributed. The Constant Phase Element (CPE) meets such a requirement. It has the form P = Y0 wn... 

Distributed Parameter Models Both non-Newtonian and shear-thinning properties of polymeric melts in particular, as well as the nonisothermal nature of the flow, significantly affect the melt extmsion process. Moreover, the non-Newtonian and nonisothermal effects interact and reinforce each other. We analyzed the non-Newtonian effect in the simple case of unidirectional parallel plate flow in Example 3.6 where Fig.E 3.6c plots flow rate versus the pressure gradient, illustrating the effect of the shear-dependent viscosity on flow rate using a Power Law model fluid. These curves are equivalent to screw characteristic curves with the cross-channel flow neglected. The Newtonian straight lines are replaced with S-shaped curves. 

Geoigakopoulos, D., Homick, M., and Sheth, A. (1995), An Overview of Workflow Management From Process Modeling to Workflow Automation Infrastructure, Distributed and Parallel Databases, Vol. B, No. 2, pp. 119-153. 

Neural networks, also called connectionist or distributed/parallel processing models, have been studied for many years in an attempt to mirror the learning and prediction abilities of human beings. 

Distributed environment (collaborative manufacturing), 604, 607-616 Distributed group decision support systems, 145 Distributed Operator Model Architecture (DOMAR), 2440-2441 Distributed/parallel processing model, see Neural networks... 

Ro WW, Gaudiot J-L (2004) SPEAR a hybrid model for speculative pre-execution. In Proceedings of the 18th international parallel and distributed processing symposium,... 

Step 4 of the thermal treatment process (see Fig. 2) involves desorption, pyrolysis, and char formation. Much Hterature exists on the pyrolysis of coal (qv) and on different pyrolysis models for coal. These models are useful starting points for describing pyrolysis in kilns. For example, the devolatilization of coal is frequently modeled as competing chemical reactions (24). Another approach for modeling devolatilization uses a set of independent, first-order parallel reactions represented by a Gaussian distribution of activation energies (25). 

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