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— The exchange of independent information between two nodes in a wireless network can be viewed as two unicast sessions, corresponding to information transfer along one direction and the opposite direction. In this paper we show such information exchange can be efficiently performed by exploiting network coding and the physical-layer broadcast property(More)
This paper proposes a face recognition system, based on probabilistic decision-based neural networks (PDBNN). With technological advance on microelectronic and vision system, high performance automatic techniques on biometric recognition are now becoming economically feasible. Among all the biometric identification methods, face recognition has attracted(More)
In this paper, the network planning problem in wireless ad hoc networks is formulated as economically allocating information carrier supplies such that certain end-to-end communication demands, as a collection of multicast sessions, are fulfilled. This formulation necessitates a cross-layer coupling. We aim at a computational characterization of the(More)
The minimum energy required to transmit a bit of information through a network characterizes the most economical way to communicate in a network. In this paper, we show that under a simplified layered model of wireless networks, the minimum-energy multicast problem in mobile ad hoc networks is solvable as a linear program, assuming network coding. Compared(More)
Supervised learning networks based on a decision-based formulation are explored. More specifically, a decision-based neural network (DBNN) is proposed, which combines the perceptron-like learning rule and hierarchical nonlinear network structure. The decision-based mutual training can be applied to both static and temporal pattern recognition problems. For(More)
This paper considers the problem of communicating correlated information from multiple source nodes over a network of noiseless channels to multiple destination nodes, where each destination node wants to recover all sources. The problem involves a joint consideration of distributed compression and network information relaying. Although the optimal rate(More)
This paper proposes to incorporate full covariance matrices into the radial basis function (RBF) networks and to use the expectation-maximization (EM) algorithm to estimate the basis function parameters. The resulting networks, referred to as elliptical basis function (EBF) networks, are evaluated through a series of text-independent speaker verification(More)
A central issue in practically deploying network coding in a shared network is the adaptive and efficient allocation of network resources. This issue can be formulated as an optimization problem of maximizing the net-utility — the difference between a utility derived from the attainable multicast throughput and the total cost of resource provisioning.(More)