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In this paper we develop a multi-agent simulation model to explore the issue of learning in interorganizational networks. Though interorganizational network researchers generally agree that when firms form into networks they will gain access to new knowled ...
Ultrasonic motors are a good alternative to electromagnetic motors in medical robotics, since they are electromagnetically compatible. Estimating speed instead of using encoders reduces cost and dimension of the robot on the one hand and increases reliabil ...
Analytic queueing network models often assume infinite capacity for all queues. For real systems this infinite capacity assumption does not hold, but is often maintained due to the difficulty of grasping the between-queue correlation structure present in f ...
Distributed adaptive algorithms are proposed based on incremental and diffusion strategies. Adaptation rules that are suitable for ring topologies and general topologies are described. Both distributed LMS and RLS implementations are considered in order to ...
In this paper, we extend the Hopfield Associative Memory for storing multiple sequences of varying duration. We apply the model for learning, recognizing and encoding a set of human gestures. We measure systematically the performance of the model against n ...
The influence of the properties of commercial powders on the densification during their packing, compaction and sintering process is still not understood in detail. With regard to the sintering process, neither the well-known sintering equation for the fir ...
A cellular hardware implementation of a spiking neural network with run-time reconfigurable connectivity is presented. It is implemented on a compact custom FPGA board which provides a powerful reconfigurable hardware platform for hardware and software des ...
This is the second episode of the Bayesian saga started with the tutorial on the Bayesian probability. Its aim is showing in very informal terms how supervised learning can be interpreted from the Bayesian viewpoint. The focus is put on supervised learning ...
Motivated by biological neural networks and distributed sensing networks, we study how pooling networks – or quantizers – with random thresholds can be used in detection tasks. We provide a brief overview of the use of deterministic quantizers in detection ...
We have monitored and analyzed, through remote sensing and ancillary field surveys, the rapid (O(1) year) development of a tidal network within a newly established artificial salt marsh in the Venice Lagoon. After the construction of the salt marsh, a netw ...