Results of the synthesis of optimal networks of AND and OR gates for four-variable switching functions by a branch-and-bound computer program /

Bibliography: p. 39 (2d group)

Optimum network design using NOR-OR gates by integer programming.

"Supported in part by ... Grant no. NSF GJ-503."

Level-restricted NOR network transduction procedures /

"UILU-ENG 77 1703."

Cost effective priority assignment in network computers,

"Supported in part by the National Science Foundation under grant no. NSF GJ 28289."

Impact of local library systems on the national networking environment : proceedings of the Library of Congress Network Advisory Committee Meeting, April 1-3, 1991.

Includes bibliographical references.

DARPA neural network study final report /

Mode of access: Internet.

Common command language for file manipulation and network job execution : an example /

Includes bibliographical references (p. 27).

Classical simulation of quantum many-body systems with a tree tensor network

We show how to efficiently simulate a quantum many-body system with tree structure when its entanglement (Schmidt number) is small for any bipartite split along an edge of the tree. As an application, we show that any one-way quantum computation on a tree graph can be efficiently simulated with a classical computer.

PROST: A programmable structured peer-to-peer overlay network

We present the idea of a programmable structured P2P architecture. Our proposed system allows the key-based routing infrastructure, which is common to all structured P2P overlays, to be shared by multiple applications. Furthermore, our architecture allows the dynamic and on-demand deployment of new applications and services on top of the shared routing layer.

An FPGA network architecture for accelerating 3DES - CBC

This paper presents a DES/3DES core that will support cipher block chaining (CBC) and also has a built in keygen that together take up about 10% of the resources in a Xilinx Virtex II 1000-4. The core will achieve up to 200Mbit/s of encryption or decryption. Also presented is a network architecture that will allow these CBC capable 3DES cores to perform their processing in parallel.

Tracking the states of a nonlinear system in the weight-space of a feed-forward neural network

Nonlinear, non-stationary signals are commonly found in a variety of disciplines such as biology, medicine, geology and financial modeling. The complexity (e.g. nonlinearity and non-stationarity) of such signals and their low signal to noise ratios often make it a challenging task to use them in critical applications. In this paper we propose a new neural network based technique to address those problems. We show that a feed forward, multi-layered neural network can conveniently capture the states of a nonlinear system in its connection weight-space, after a process of supervised training. The performance of the proposed method is investigated via computer simulations.