Implementation of a Modified Counterpropagation Neural Network Model in Online Handwritten Character Recognition System

Artificial neural networks are one of the widely used automated techniques. Though they yield high accuracy, most of the neural networks are computationally heavy due to their iterative nature. Hence, there is a significant requirement for a neural classifier which is computationally efficient and highly accurate. To this effect, a modified Counter Propagation Neural Network (CPN) is employed in this work which proves to be faster than the conventional CPN. In the modified CPN model, there was no need of training parameters because it is not an iterative method like backpropagation architecture which took a long time for learning. This paper implemented a modified Counterpropagation neural network for recognition of online uppercase (A-Z), lowercase (a-z) English alphabets and digits (0-9). The system is tested for different handwritten character samples and better recognition accuracies of 65% to 96% were obtained compared to related work in literature.   Keywords: Artificial Neural Network, Counterpropagation Neural Network, Character Recognition, Feature Extraction

Reverse Engineering TCP/IP-like Networks using Delay-Sensitive Utility Functions

TCP/IP can be interpreted as a distributed primal-dual algorithm to maximize aggregate utility over source rates. It has recently been shown that an equilibrium of TCP/IP, if it exists, maximizes the same delay-insensitive utility over both source rates and routes, provided pure congestion prices are used as link costs in the shortest-path calculation of IP. In practice, however, pure dynamic routing is never used and link costs are weighted sums of both static as well as dynamic components. In this paper, we introduce delay-sensitive utility functions and identify a class of utility functions that such a TCP/IP equilibrium optimizes. We exhibit some counter-intuitive properties that any class of delay-sensitive utility functions optimized by TCP/IP necessarily possess. We prove a sufficient condition for global stability of routing updates for general networks. We construct example networks that defy conventional wisdom on the effect of link cost parameters on network stability and utility

A Heterosynaptic Learning Rule for Neural Networks

In this article we intoduce a novel stochastic Hebb-like learning rule for neural networks that is neurobiologically motivated. This learning rule combines features of unsupervised (Hebbian) and supervised (reinforcement) learning and is stochastic with respect to the selection of the time points when a synapse is modified. Moreover, the learning rule does not only affect the synapse between pre- and postsynaptic neuron, which is called homosynaptic plasticity, but effects also further remote synapses of the pre- and postsynaptic neuron. This more complex form of synaptic plasticity has recently come under investigations in neurobiology and is called heterosynaptic plasticity. We demonstrate that this learning rule is useful in training neural networks by learning parity functions including the exclusive-or (XOR) mapping in a multilayer feed-forward network. We find, that our stochastic learning rule works well, even in the presence of noise. Importantly, the mean learning time increases with the number of patterns to be learned polynomially, indicating efficient learning.Comment: 19 page

Two-Way Optical Frequency Comparisons Over 100km Telecommunication Network Fibers

By using two-way frequency transfer, we demonstrate ultra-high resolution comparison of optical frequencies over a telecommunication fiber link of 100 km operating simultaneously digital data transfer. We first propose and experiment a bi-directional scheme using a single fiber. We show that the relative stability at 1 s integration time is 7 10^18 and scales down to 5 10^21. The same level of performance is reached when an optical link is implemented with an active compensation of the fiber noise. We also implement a real-time two-way frequency comparison over a uni-directional telecommunication network using a pair of parallel fibers. The relative frequency stability is 10^15 at 1 s integration time and reaches 2 10^17 at 40 000 s. The fractional uncertainty of the frequency comparisons was evaluated for the best case to 2 10^20. These results open the way to accurate and high resolution frequency comparison of optical clocks over intercontinental fiber networks

A Mobile Satellite Experiment (MSAT-X) network definition

The network architecture development of the Mobile Satellite Experiment (MSAT-X) project for the past few years is described. The results and findings of the network research activities carried out under the MSAT-X project are summarized. A framework is presented upon which the Mobile Satellite Systems (MSSs) operator can design a commercial network. A sample network configuration and its capability are also included under the projected scenario. The Communication Interconnection aspect of the MSAT-X network is discussed. In the MSAT-X network structure two basic protocols are presented: the channel access protocol, and the link connection protocol. The error-control techniques used in the MSAT-X project and the packet structure are also discussed. A description of two testbeds developed for experimentally simulating the channel access protocol and link control protocol, respectively, is presented. A sample network configuration and some future network activities of the MSAT-X project are also presented

Cascading Power Outages Propagate Locally in an Influence Graph that is not the Actual Grid Topology

In a cascading power transmission outage, component outages propagate non-locally, after one component outages, the next failure may be very distant, both topologically and geographically. As a result, simple models of topological contagion do not accurately represent the propagation of cascades in power systems. However, cascading power outages do follow patterns, some of which are useful in understanding and reducing blackout risk. This paper describes a method by which the data from many cascading failure simulations can be transformed into a graph-based model of influences that provides actionable information about the many ways that cascades propagate in a particular system. The resulting "influence graph" model is Markovian, in that component outage probabilities depend only on the outages that occurred in the prior generation. To validate the model we compare the distribution of cascade sizes resulting from $n-2$ contingencies in a $2896$ branch test case to cascade sizes in the influence graph. The two distributions are remarkably similar. In addition, we derive an equation with which one can quickly identify modifications to the proposed system that will substantially reduce cascade propagation. With this equation one can quickly identify critical components that can be improved to substantially reduce the risk of large cascading blackouts.Comment: Accepted for publication at the IEEE Transactions on Power System

Unusual magnetic-field dependence of partially frustrated triangular ordering in manganese tricyanomethanide

Manganese tricyanomethanide, Mn[C(CN)3]2, consists of two interpenetrating three-dimensional rutile-like networks. In each network, the tridentate C(CN)3- anion gives rise to superexchange interactions between the Mn2+ ions (S=5/2) that can be mapped onto the "row model" for partially frustrated triangular magnets. We present heat capacity measurements that reveal a phase transition at T_N = 1.18K, indicative of magnetic ordering. The zero-field magnetically ordered structure was solved from neutron powder diffraction data taken between 0.04 and 1.2 K. It consists of an incommensurate spiral with a temperature independent propagation vector Q=(2Q 0 0)=(+/-0.622 0 0), where different signs relate to the two different networks. This corresponds to (+/-0.311 +/-0.311 0) in a quasi-hexagonal representation. The ordered moment mu=3.3mu_B is about 2/3 of the full Mn2+ moment. From the values of T_N and Q, the exchange parameters J/k = 0.15 K and J'/J = 0.749 are estimated. The magnetic-field dependence of the intensity of the Bragg reflection, measured for external fields H||Q, indicates the presence of three different magnetic phases. We associate them with the incommensurate spiral (H < 13.5 kOe), an intermediate phase (13.5 kOe 16 kOe) proposed for related compounds. For increasing fields, Q continuously approaches the value 1/3, corresponding to the commensurate magnetic structure of the fully frustrated triangular lattice. This value is reached at H_c = 19 kOe. At this point, the field-dependence reverses and Q adopts a value of 0.327 at 26 kOe, the highest field applied in the experiment. Except for H_c, the magnetic ordering is incommensurate in all three magnetic phases of Mn[C(CN)3]2.Comment: accepted for publication in J. Phys.: Condens. Matte