We analyse individual components of this network, organized into three network architectures, and describe the frequency-decoding capabilities of each of these modules.
This was done by examining the performance of the three network architectures and training algorithms using both raw and transformed data.
The Internet Engineering Task Force (IETF) defined two network architecture approaches to meet the QoS requirements for applications communicating in data networks, the integrated service (IntServ) [16] and DiffServ [17, 18] networks.
The 802.11 standard specifies two network architectures: Infrastructure Basic Service Set (BSS) and Independent BSS (IBSS).
Two network architectures based on one stage and two stage feed forward neural networks are chosen for this investigation.
This paper presents two network architectures with associated routing and multicast algorithms for improved performance under multicasting traffic conditions.
We ran simulation experiments to study memory recall in two network architectures: one interconnected pool of cells, and two reciprocally connected pools.
Performance of the two network architectures is studied by means of computer simulation in terms of their queuing delay, node throughput and proportion of packets dropped.
This algorithm has two network architectures (one optimised for speed (FST), other for accuracy (ACRT)).
Summarily, comparison between two network architectures is given in Table 1.
A major finding of this study is the identification of two network architectures, with either a gradient of local connectivity or a gradient of long-distance connection length, that give rise to activity patterns with localized timescales.
