A new design method for the complex-valued multistate Hopfield associative memory

A method to store each element of an integral memory set M subset {1,2,...,K}/sup n/ as a fixed point into a complex-valued multistate Hopfield network is introduced. The method employs a set of inequalities to render each memory pattern as a strict local minimum of a quadratic energy landscape. Based on the solution of this system, it gives a recurrent network of n multistate neurons with complex and symmetric synaptic weights, which operates on the finite state space {1,2,...,K}/sup n/ to minimize this quadratic functional. Maximum number of integral vectors that can be embedded into the energy landscape of the network by this method is investigated by computer experiments. This paper also enlightens the performance of the proposed method in reconstructing noisy gray-scale images.     

Atmospheric concentrations, dry deposition and air-soil exchange of polycyclic aromatic hydrocarbons (PAHs) in an industrial region in Turkey

Concurrent ambient air and dry deposition samples were collected during two sampling periods at the Aliaga industrial region in Izmir, Turkey. Sigma 15-PAH (particulate+gas) concentrations ranged between 7.3 and 44.8 ng m(-3) (average+/-S.D., 25.2+/-8.8 ng m(-3)) and 10.2-71.9 ng m(-3) (44.1+/-16.6 ng m(-3)) in summer and winter, respectively. Winter/summer individual ambient PAH concentration ratios ranged between 0.8 (acenaphthene) and 6.6 (benz[a]anthracene) indicating that wintertime concentrations were affected by residential heating emissions. In contrast to the ambient concentrations, summation operator(15)-PAH particle dry deposition fluxes were higher in summer (5792+/-3516 ng m(-2)day(-1), average+/-S.D.) than in winter (2650+/-1829 ng m(-2)day(-1)), probably due to large particles from enhanced re-suspension of polluted soil particles and road dust. Average overall dry deposition velocity of PAHs calculated using the dry deposition fluxes and particle-phase concentrations was 2.9+/-3.5 cm s(-1). summation operator(15)-PAH concentrations in soils taken from 50 points in the area ranged between 11 and 4628 microg kg(-1) in dry weight. The spatial distribution of these concentrations indicated that the urban Aliaga, steel plants, the petroleum refinery, and the petrochemical plant are the major Sigma 15-PAH sources in the area. Fugacity calculations in air and soil showed that the soil acts as a secondary source to the atmosphere for low molecular weight PAHs in summer and as a sink for the higher molecular weight ones in summer and winter.     

An energy function-based design method for discrete hopfield associative memory with attractive fixed points

An energy function-based autoassociative memory design method to store a given set of unipolar binary memory vectors as attractive fixed points of an asynchronous discrete Hopfield network (DHN) is presented. The discrete quadratic energy function whose local minima correspond to the attractive fixed points of the network is constructed via solving a system of linear inequalities derived from the strict local minimality conditions. The weights and the thresholds are then calculated using this energy function. If the inequality system is infeasible, we conclude that no such asynchronous DHN exists, and extend the method to design a discrete piecewise quadratic energy function, which can be minimized by a generalized version of the conventional DHN, also proposed herein. In spite of its computational complexity, computer simulations indicate that the original method performs better than the conventional design methods in the sense that the memory can store, and provide the attractiveness for almost all memory sets whose cardinality is less than or equal to the dimension of its elements. The overall method, together with its extension, guarantees the storage of an arbitrary collection of memory vectors, which are mutually at least two Hamming distances away from each other, in the resulting network.     

A Boolean Hebb rule for binary associative memory design

A binary associative memory design procedure that gives a Hopfield network with a symmetric binary weight matrix is introduced in this paper. The proposed method is based on introducing the memory vectors as maximal independent sets to an undirected graph, which is constructed by Boolean operations analogous to the conventional Hebb rule. The parameters of the resulting network is then determined via the adjacency matrix of this graph in order to rind a maximal independent set whose characteristic vector is close to the given distorted vector. We show that the method provides attractiveness for each memory vector and avoids spurious memories whenever the set of given memory vectors satisfy certain compatibility conditions, which implicitly imply sparsity. The applicability of the design method is finally investigated by a quantitative analysis of the compatibility conditions.     

Using clinical information in goal-oriented learning.

We have proposed an extension to the Q-learning algorithm that incorporates the existing clinical expertise into the trial-and-error process of acquiring an appropriate administration strategy of rHuEPO to patients with anemia due to ESRD. The specific modification lies in multiple updates of the Q-values for several dose/response combinations during a single learning event. This in turn decreases the risk of administering doses that are inadequate in certain situations and thus increases the speed of the learning process. We have evaluated the proposed method using a simulation test-bed involving an "artificial patient" and compared the outcomes to those obtained by a classical Q-learning and a numerical implementation of a clinically used administration protocol for anemia management. The outcomes of the simulated treatments demonstrate that the proposed method is a more effective tool than the traditional Q-learning. Furthermore, we have observed that it has a potential to provide even more stable anemia management than the AMP.