R. Hecht-Nielsen. Neurocomputing: picking the human brain. IEEE Spectrum, 25(3):36--41, March 1988.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....Neumann memory) The microcode for the REKURSIV Lingo factorial example: n factorial [ i x ] if n = 0 then 1 else i : n 1; x : n; while i 0 do x : x i; i : i 1; x . Smalltalk factorial example: factorial self 0 ifTrue: self (self 1) factorial ] self = 0 ifTrue: [1]. self error: factorial invalid for: self printString Figure 2: Sample Lingo and Smalltalk source code examples. can manipulate arbitrarily structured data and paging is performed automatically (i.e. backing up of an instruction is not necessary) with the page faults being handled by the ....

R. Hecht-Nielsen. Neurocomputing: picking the human brain. IEEE Spectrum, 25(3):36--41, March 1988.

....of scene partitioning and invariant target recognition. Neural nets have succesfully been applied to translation (e.g. Fukushima, 1980; Rosenblatt, 1961) orientation and scale (Reitboeck and Altmann, 1984; Carpenter et al. 1989; Gupta and Sayeh, 1988) invariant target recognition (seee also Hecht Nielsen, 1988). 3 DIGITAL IMAGE REPRESENTATIONS A two dimensional digital image is represented by a function f(x; y) of two variables x and y that represent the spatial coordinates in the image plane. The value of f represents the local brightness (intensity) or k tuples of brightness values in case of ....

Hecht-Nielsen, R. (1988). Neurocomputing: picking the human brain. In: Artificial neural networks: theoretical concepts. Vemuri, V. (ed.). IEEE Comp. Soc. Press, Washington.

....technique combining sufficient flexibility with acceptable cost. Flexibility is essential, due to the different mathematical models underlying neural nets, the different network architectures and applications and also due to the experimental character of most research projects (cf. e.g. [12, 15, 9, 1, 16]) Different simulators serve different purposes ranging from modeling bio chemical processes in the human brain (e.g. 17] to developing structured connectionist models of artificial memory, recognition and reasoning processes (e.g. 8, 11, 3] Efficiency is equally important; the simulation of ....

Hecht-Nielson, R.: Neurocomputing: Picking the Human Brain. IEEE Spectrum, March 1988, pp. 36--41

.... applies, i.e. there is no more learning (see figure 4 (a) Mapping Assigning a neural network simulation model to a parallel architecture is a very skilful task, as there are obviously no appropriate target machines (an overview of upcoming neural network simulation machines and prototypes is [Hech 88] due to technological limitations to build simple processing elements with high degree of connectivity. For simulating multi layer neural networks on a transputer based multiprocessor system we identify temporal parallelism as input patterns can walk through the net in a pipeline . ....

R. Hecht-Nielsen. "Neurocomputing: picking the human brain". IEEE Spectrum, Vol. 25, No. 3, pp. 36--41, March 1988.

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Robert Hecht-Nielsen, "Neurocomputing: picking the human brain", IEEE Spectrum, volume 25, number 3, pages 36-41, March 1988.

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