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Shelton, Robert O.

Publications and source records attributed to Shelton, Robert O..

21 records · Page 2

Method and apparatus for preloading a joint by remotely operable means

The invention is a method and apparatus for joining structures, an active structure and a passive structure, and imposing a tensile pre-load on the joint by a remotely operable mechanism comprising a heat contractible joining element. The method and apparatus include mounting on the structure, a probe shaft of material which is transformable from an expanded length to a contracted length when heated to a specific temperature range. The shaft is provided with a probe head which is receivable in a receptacle opening formed in the passive structure, when the active structure is moved into engagement therewith by an appropriate manipulator mechanism. A latching system mounted on the structure adjacent to the receptacle opening captures the probe head, when the probe head is inserted a predetermined amount. A heating coil on the shaft is energizable by remote control for heating the shaft to a temperature range which transforms the shaft to its contracted length, whereby a latching shoulder thereof engages latching elements of the latching system and imposes a tensile preload on the structural joint. Provision is also made for manually adjusting the probe head on the shaft to allow for manual detachment of the structures or manual preloading of the structural joint.

Shelton, Robert O.↗

Method Accelerates Training Of Some Neural Networks

Three-layer networks trained faster provided two conditions are satisfied: numbers of neurons in layers are such that majority of work done in synaptic connections between input and hidden layers, and number of neurons in input layer at least as great as number of training pairs of input and output vectors. Based on modified version of back-propagation method.

Shelton, Robert O.↗

A space-time neural network

Introduced here is a novel technique which adds the dimension of time to the well known back propagation neural network algorithm. Cited here are several reasons why the inclusion of automated spatial and temporal associations are crucial to effective systems modeling. An overview of other works which also model spatiotemporal dynamics is furnished. A detailed description is given of the processes necessary to implement the space-time network algorithm. Several demonstrations that illustrate the capabilities and performance of this new architecture are given.

Villarreal, James A.↗