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C A Pomalaza-Raez

Publications and source records attributed to C A Pomalaza-Raez.

4 recordsLinked to original sources
PubMed1996

Determination of dependent and independent communication paths using neural networks.

Efficient and timely computation of routing algorithms is very important for proper operation of multihop packet radio networks. When a network operates in the presence of jammers (a hostile environment) additional constraints must be considered when computing the routing tables. Insertion of those constraints in routing algorithms enables the determination of dependent and independent paths between source and destination nodes, thus fixing lower limits on the number of external jamming sources required to sever a transmission. An important measure of network reliability is also provided. This paper proposes a solution to the routing problem through the implementation of a Hopfield network and demonstrates that by proper selection of an energy function we can solve the problem rapidly and reliably.

Algorithms↗
PubMed1996

Using neural networks to solve the multicast routing problem in packet radio networks.

The primary function of a packet radio network is the efficient transfer of information between source and destination nodes using minimal bandwidth and end-to-end delay. Many researchers have investigated the problem of minimizing the end-to-end delay from a single source to a single destination for a variety of networks; however, very little work is reported about routing mechanisms for the common case where a particular information packet is intended to be sent to more than one destination in the network. This is known as multicasting. A simplified version of the problem is to ignore the packet delay at each node, then the problem becomes one of finding solutions which require the least number of transmissions. Determination of an optimal solution is NP-complete meaning that suboptimal solutions are frequently tolerated. The problem becomes more rigorous if packet delays are included in the network topology. This paper describes a practical technique for the computation of optimum or near optimum solutions to the multicasting problem with and without packet delay. The method is based on the Hopfield neural network and experiment has shown this method to yield near optimal solutions while requiring a minimum of CPU time.

Algorithms↗
PubMed1989

The use of nonuniform element spacing in array processing algorithms.

Most array signal processing algorithms use uniform element spacing to estimate source bearing. This paper demonstrates the benefit of using nonuniform element spacing in Bartlett, linear prediction (LP), and minimum variance (MV) array processing algorithms. By using optimum element spacing results obtained by previous investigators for sidelobe reduction of the Bartlett method, better MV and LP performances, in terms of array output power, are obtained.

Algorithms↗