Competitive learning and soft competition for vector quantizerdesign

The authors provide a convergence analysis for the Kohonen learning algorithm (KLA) with respect to vector quantizer (VQ) optimality criteria and introduce a stochastic relaxation technique which produces the global minimum but is computationally expensive. By incorporating the principles of the stochastic approach into the KLA, a deterministic VQ design algorithm, the soft competition scheme (SCS), is introduced. Experimental results are presented where the SCS consistently provided better codebooks than the generalized Lloyd algorithm (GLA), even when the same computation time was used for both algorithms. The SCS may therefore prove to be a valuable alternative to the GLA for VQ design     

Globally optimal vector quantizer design by stochastic relaxation

The authors present a unified formulation and study of vector quantizer design methods that couple stochastic relaxation (SR) techniques with the generalized Lloyd algorithm. Two new SR techniques are investigated and compared: simulated annealing (SA) and a reduced-complexity approach that modifies the traditional acceptance criterion for simulated annealing to an unconditional acceptance of perturbations. It is shown that four existing techniques all fit into a general methodology for vector quantizer design aimed at finding a globally optimal solution. Comparisons of the algorithms' performances when quantizing Gauss-Markov processes, speech, and image sources are given. The SA method is guaranteed to perform in a globally optimal manner, and the SR technique gives empirical results equivalent to those of SA. Both techniques result in significantly better performance than that obtained with the generalized Lloyd algorithm     

Transport properties of alkanes through ceramic thin zeolite MFI membranes

Polycrystalline randomly oriented defect free zeolite layers on porous α-Al₂O₃ supports are prepared with a thickness of less than 5 μm by in situ crystallisation of silicalite-1. The flux of alkanes is a function of the sorption and intracrystalline diffusion. In mixtures of strongly and weakly adsorbing gases and a high loadings of the strongly adsorbing molecule in the zeolite poze, the flux of the weakly adsorbing molecule is suppressed by the sorption and the mobility of the strongly adsorbing molecule resulting in pore-blocking effects. The separation of these mixtures is mainly based on the sorption and completely different from the permselectivity. At low loadings of the strongly adsorbing molecules the separation is based on the sorption and the diffusion and is the same as the permselectivity. Separation factors for the isomers of butane (n-butane/isobutane) and hexane (hexane/2,2-dimethylbutane) are respectively high (10) and very high (> 2000) at 200°C. These high separation factors are a strong evidence that the membrane shows selectivity by size-exclusion and that transport in pores larger than the zeolite MFI pores (possible defects, etc) can be neglected.     

The impact of alkali elements on the degradation of CIGS solar cells

Unencapsulated CIGS solar cells with high and low contents of sodium (Na) and potassium (K) were simultaneously exposed to damp heat and illumination. The solar cells with a high alkali (Na, K) content exhibited higher initial conversion efficiencies, but degraded severely within 100 h, while the alkali poor samples kept relatively stable performance under damp heat and illumination. The degradation of the samples with a high alkali content resulted in the formation of sodium rich spots on the top ZnO:Al surface of the samples. This is likely caused by light‐induced Na⁺ migration via the grain boundaries in the absorber to the depletion region, where the Na⁺ accumulated. This allowed subsequent Na⁺ transport through the depletion region due to the lowering of the internal electric field caused both by the Na⁺ accumulation and illumination. The migration resulted in the formation of shunt paths, which reduced the shunt resistance and open circuit voltage. Furthermore, ingression of water into the ZnO:Al is expected to be responsible for a slow but steady increase in series resistance for both high and low alkali solar cells. Additionally, sodium migration led to a severe increase of the series resistance in case of alkali rich samples. Copyright © 2015 John Wiley & Sons, Ltd.     

Networks, Matroids, and Non-Shannon Information Inequalities

We define a class of networks, called matroidal networks, which includes as special cases all scalar-linearly solvable networks, and in particular solvable multicast networks. We then present a method for constructing matroidal networks from known matroids. We specifically construct networks that play an important role in proving results in the literature, such as the insufficiency of linear network coding and the unachievability of network coding capacity. We also construct a new network, from the Vamos matroid, which we call the Vamos network, and use it to prove that Shannon-type information inequalities are in general not sufficient for computing network coding capacities. To accomplish this, we obtain a capacity upper bound for the Vamos network using a non-Shannon-type information inequality discovered in 1998 by Zhang and Yeung, and then show that it is smaller than any such bound derived from Shannon-type information inequalities. This is the first application of a non-Shannon-type inequality to network coding. We also compute the exact routing capacity and linear coding capacity of the Vamos network. Finally, using a variation of the Vamos network, we prove that Shannon-type information inequalities are insufficient even for computing network coding capacities of multiple-unicast networks.     

Insufficiency of linear coding in network information flow

It is known that every solvable multicast network has a scalar linear solution over a sufficiently large finite-field alphabet. It is also known that this result does not generalize to arbitrary networks. There are several examples in the literature of solvable networks with no scalar linear solution over any finite field. However, each example has a linear solution for some vector dimension greater than one. It has been conjectured that every solvable network has a linear solution over some finite-field alphabet and some vector dimension. We provide a counterexample to this conjecture. We also show that if a network has no linear solution over any finite field, then it has no linear solution over any finite commutative ring with identity. Our counterexample network has no linear solution even in the more general algebraic context of modules, which includes as special cases all finite rings and Abelian groups. Furthermore, we show that the network coding capacity of this network is strictly greater than the maximum linear coding capacity over any finite field (exactly 10% greater), so the network is not even asymptotically linearly solvable. It follows that, even for more general versions of linearity such as convolutional coding, filter-bank coding, or linear time sharing, the network has no linear solution.     

Stochastic relaxation algorithm for improved vector quantiser design

An easily implementable stochastic relaxation algorithm for vector quantisation design is given. It generalises the usual Lloyd iteration in codebook design by perturbing the computed centroids with independent multidimensional noise, whose variance diminishes as the algorithm progresses. A significant improvement is often achieved.<>     

Analysis of an industrial component commonality problem

We discuss a case study of an industrial production-marketing coordination problem involving component commonality. For the product line considered, the strategic goal of the company is to move from the current low volume market to a high volume market. The marketing department believes that this can be achieved by substantially lowering the end products’ prices. However, this requires a product redesign to lower production costs in order to maintain profit margins. The redesign decision involves grouping end products into families. All products within one family use the same version of some components. This paper fits in the stream of recent literature on component commonality where the focus has shifted from inventory cost savings to production and development cost savings. Further, we consider both costs and revenues, leading to a profit maximization approach. The price elasticity of demand determines the relationship between the price level and number of units sold. Consequently, we integrate information from different functional areas such as production, marketing and accounting. We formulate the problem as a net-present-value investment decision. We propose a mixed integer nonlinear optimization model to find the optimal commonality decision. The recommendation based on our analysis has been implemented in the company. In addition, the application allows us to experimentally validate some claims made in the literature and obtain managerial insights into the trade-offs.