Simple adaptive momentum: new algorithm for training multilayer perceptrons

The speed of convergence while training is an important consideration in the use of neural nets. The authors outline a new training algorithm which reduces both the number of iterations and training time required for convergence of multilayer perceptrons, compared to standard back-propagation and conjugate gradient descent algorithms.

Stable linearization using multilayer neural networks

The main limitation of linearization theory that prevents its application in practical problems is the need for an exact knowledge of the plant. This requirement is eliminated and it is shown that a multilayer network can synthesise the state feedback coefficients that linearize a nonlinear control affine plant. The stability of the linearizing closed loop can be guaranteed if the autonomous plant is asymptotically stable and the state feedback is bounded.

Nonlinear stability of multilayer quasi-geostrophic flow

New nonlinear stability theorems are derived for disturbances to steady basic flows in the context of the multilayer quasi-geostrophic equations. These theorems are analogues of Arnol’d's second stability theorem, the latter applying to the two-dimensional Euler equations. Explicit upper bounds are obtained on both the disturbance energy and disturbance potential enstrophy in terms of the initial disturbance fields. An important feature of the present analysis is that the disturbances are allowed to have non-zero circulation. While Arnol’d's stability method relies on the energy–Casimir invariant being sign-definite, the new criteria can be applied to cases where it is sign-indefinite because of the disturbance circulations. A version of Andrews’ theorem is established for this problem, and uniform potential vorticity flow is shown to be nonlinearly stable. The special case of two-layer flow is treated in detail, with particular attention paid to the Phillips model of baroclinic instability. It is found that the short-wave portion of the marginal stability curve found in linear theory is precisely captured by the new nonlinear stability criteria.

Automated algorithms for multilayer thin film filter design using metamaterials

Currently, infrared filters for astronomical telescopes and satellite radiometers are based on multilayer thin film stacks of alternating high and low refractive index materials. However, the choice of suitable layer materials is limited and this places limitations on the filter performance that can be achieved. The ability to design materials with arbitrary refractive index allows for filter performance to be greatly increased but also increases the complexity of design. Here a differential algorithm was used as a method for optimised design of filters with arbitrary refractive indices, and then materials are designed to these specifications as mono-materials with sub wavelength structures using Bruggeman’s effective material approximation (EMA).

Mid-infrared filters for astronomical and remote sensing instrumentation

As improvements to the optical design of spectrometer and radiometer instruments evolve with advances in detector sensitivity, use of focal plane detector arrays and innovations in adaptive optics for large high altitude telescopes, interest in mid-infrared astronomy and remote sensing applications have been areas of progressive research in recent years. This research has promoted a number of developments in infrared coating performance, particularly by placing increased demands on the spectral imaging requirements of filters to precisely isolate radiation between discrete wavebands and improve photometric accuracy. The spectral design and construction of multilayer filters to accommodate these developments has subsequently been an area of challenging thin-film research, to achieve high spectral positioning accuracy, environmental durability and aging stability at cryogenic temperatures, whilst maximizing the far-infrared performance. In this paper we examine the design and fabrication of interference filters in instruments that utilize the mid-infrared N-band (6-15 µm) and Q-band (16-28 µm) atmospheric windows, together with a rationale for the selection of materials, deposition process, spectral measurements and assessment of environmental durability performance.

The radiative effect of a fir canopy on a snowpack

Models of snow processes in areas of possible large-scale change need to be site independent and physically based. Here, the accumulation and ablation of the seasonal snow cover beneath a fir canopy has been simulated with a new physically based snow-soil vegetation-atmosphere transfer scheme (Snow-SVAT) called SNOWCAN. The model was formulated by coupling a canopy optical and thermal radiation model to a physically based multilayer snow model. Simple representations of other forest effects were included. These include the reduction of wind speed and hence turbulent transfer beneath the canopy, sublimation of intercepted snow, and deposition of debris on the surface. This paper tests this new modeling approach fully at a fir site within Reynolds Creek Experimental Watershed, Idaho. Model parameters were determined at an open site and subsequently applied to the fir site. SNOWCAN was evaluated using measurements of snow depth, subcanopy solar and thermal radiation, and snowpack profiles of temperature, density, and grain size. Simulations showed good agreement with observations (e.g., fir site snow depth was estimated over the season with r(2) = 0.96), generally to within measurement error. However, the simulated temperature profiles were less accurate after a melt-freeze event, when the temperature discrepancy resulted from underestimation of the rate of liquid water flow and/or the rate of refreeze. This indicates both that the general modeling approach is applicable and that a still more complete representation of liquid water in the snowpack will be important.

High performance blocking filters for the region 1µm to 20µm

A set of filters based on the sequence of semiconductor edges is described which offers continuity of short-wave infrared blocking. The rejection throughout the stop region is greater than 103 for each filter and the transmission better than 70% through one octave with a square cutoff. The cutoff points are located at intervals of about two-thirds of an octave. Filters at 2.6 ,µm, 5.5 µm, and 12 µm which use a low-passing multilayer in combination with a semiconductor absorption edge are described in detail. The design of multilayers for optimum performance is discussed by analogy with the synthesis of electric circuit filters.

Statistical downscaling of river flows

An extensive statistical ‘downscaling’ study is done to relate large-scale climate information from a general circulation model (GCM) to local-scale river flows in SW France for 51 gauging stations ranging from nival (snow-dominated) to pluvial (rainfall-dominated) river-systems. This study helps to select the appropriate statistical method at a given spatial and temporal scale to downscale hydrology for future climate change impact assessment of hydrological resources. The four proposed statistical downscaling models use large-scale predictors (derived from climate model outputs or reanalysis data) that characterize precipitation and evaporation processes in the hydrological cycle to estimate summary flow statistics. The four statistical models used are generalized linear (GLM) and additive (GAM) models, aggregated boosted trees (ABT) and multi-layer perceptron neural networks (ANN). These four models were each applied at two different spatial scales, namely at that of a single flow-gauging station (local downscaling) and that of a group of flow-gauging stations having the same hydrological behaviour (regional downscaling). For each statistical model and each spatial resolution, three temporal resolutions were considered, namely the daily mean flows, the summary statistics of fortnightly flows and a daily ‘integrated approach’. The results show that flow sensitivity to atmospheric factors is significantly different between nival and pluvial hydrological systems which are mainly influenced, respectively, by shortwave solar radiations and atmospheric temperature. The non-linear models (i.e. GAM, ABT and ANN) performed better than the linear GLM when simulating fortnightly flow percentiles. The aggregated boosted trees method showed higher and less variable R2 values to downscale the hydrological variability in both nival and pluvial regimes. Based on GCM cnrm-cm3 and scenarios A2 and A1B, future relative changes of fortnightly median flows were projected based on the regional downscaling approach. The results suggest a global decrease of flow in both pluvial and nival regimes, especially in spring, summer and autumn, whatever the considered scenario. The discussion considers the performance of each statistical method for downscaling flow at different spatial and temporal scales as well as the relationship between atmospheric processes and flow variability.

An electrochemical study of 4-aminothiophenol/pt nanoparticle multilayers on gold electrodes

Quartz crystal microbalance (QCM) measurements of the formation of a 4-aminothiophenol (4-ATP)self-assembled monolayer (SAM) at a gold electrode showed that a surface coverage of 118 ng cm(-2) was obtained after a 3 h exposure period, indicating that good surface coverage was achieved. Cyclic voltammetry of the ferricyanide redox couple across this SAM modified surface produced similar results to those of a bare electrode; however, the electroreduction of oxygen was found to be impaired. The 4-ATP SAM layer was not stable to repeated electrochemical oxidation and reduction; it is believed that the 4-ATP SAM layer was first converted to a 4'-mercapto-N-phenylquinone diimine (NPQD) layer followed by subsequent formation of a 4'-mercapto-N-phenylquinone monoimine (NPQM) layer. We also report a quartz crystal microbalance study of the attachment of platinum nanoparticles to such SAM modified electrodes. We show that five times the amount of platinum nanoparticles can be attached to a 4-ATP modified electrode surface (observed frequency change - 187 Hz) compared with an NPQD modified electrode surface (observed frequency change -35 Hz). The presence of the platinum particles was confirmed electrochemically by their surface electrochemical properties, which were different from those of the underlying gold electrode. It is believed that this is the first time that such direct evidence of electrochemical communication between platinum nanoparticles and a SAM modified electrode surface has been obtained. It was also shown to be possible to build up multilayer SAM/nanoparticle modified surfaces while maintaining efficient electrochemical communication. Up to three SAM/nanoparticle sandwich layers were constructed.

The local adsorption geometry and electronic structure of alanine on Cu{110}

The adsorption of alanine on Cu {110} was studied by a combination of near edge X-ray absorption fine structure (NEXAFS) spectroscopy, X-ray photoelectron spectroscopy (XPS) and density functional theory (DFT). Large chemical shifts in the C 1s, N 1s, and O 1s XP spectra were found between the alanine multilayer and the chemisorbed and pseudo-(3 x 2) alaninate layers. From C, N, and O K-shell NEXAFS spectra the tilt angles of the carboxylate group (approximate to 26 degrees in plane with respect to [1 (1) over bar0] and approximate to 45 degrees out of plane) and the C-N bond angle with respect to [1 (1) over bar0] could be determined for the pseudo-(3 x 2) overlayer. Using this information three adsorption geometries could be eliminated from five p(3 x 2) structures which lead to almost identical heats of adsorption in the DFT calculations between 1.40 and 1.47 eV/molecule. Due to the small energy difference between the remaining two structures it is not unlikely that these coexist on the surface at room temperature. (c) 2006 Elsevier B.V. All rights reserved.

Adsorption of frog foam nest proteins at the air-water interface

The surfactant properties of aqueous protein mixtures ( ranaspumins) from the foam nests of the tropical frog Physalaemus pustulosus have been investigated by surface tension, two-photon excitation. uorescence microscopy, specular neutron reflection, and related biophysical techniques. Ranaspumins lower the surface tension of water more rapidly and more effectively than standard globular proteins under similar conditions. Two- photon excitation. uorescence microscopy of nest foams treated with fluorescent marker ( anilinonaphthalene sulfonic acid) shows partitioning of hydrophobic proteins into the air-water interface and allows imaging of the foam structure. The surface excess of the adsorbed protein layers, determined from measurements of neutron reflection from the surface of water utilizing H2O/D2O mixtures, shows a persistent increase of surface excess and layer thickness with bulk concentration. At the highest concentration studied ( 0.5 mg ml(-1)), the adsorbed layer is characterized by three distinct regions: a protruding top layer of similar to20 Angstrom, a middle layer of similar to30 Angstrom, and a more diffuse submerged layer projecting some 25 Angstrom into bulk solution. This suggests a model involving self-assembly of protein aggregates at the air-water interface in which initial foam formation is facilitated by specific surfactant proteins in the mixture, further stabilized by subsequent aggregation and cross-linking into a multilayer surface complex.

Interference filters and coatings for mid-infrared astronomy (8-30µm)

The VISIR instrument for the European Southern Observatory (ESO) Very Large Telescope (VLT) is a thermal-infrared imager and spectrometer currently being developed by the French Service d'Astrophysique of CEA Saclay, and Dutch NFRA ASTRON Dwingeloo consortium. This cryogenic instrument will employ precision infrared bandpass filters in the N-( =7.5-14µm) and Q-( =16-28µm) band mid-IR atmospheric windows to study interstellar and circumstellar environments crucial for star and planetary formation theories. As the filters in these mid-IR wavelength ranges are of interest to many astronomical cryogenic instruments, a worldwide astronomical filter consortium was set up with participation from 12 differing institutes, each requiring instrument specific filter operating environments and optical metrology. This paper describes the design and fabrication methods used to manufacture these astronomical consortium filters, including the rationale for the selection of multilayer coating designs, temperature-dependant optical properties of the filter materials and FTIR spectral measurements showing the changes in passband and blocking performance on cooling to <50K. We also describe the development of a 7-14µm broadband antireflection coating deposited on Ge lenses and KRS-5 grisms for cryogenic operation at 40K

Investigation of cadmium alternatives in thin-film coatings - art. no. 62860C

The health risks associated with the inhalation or ingestion of cadmium are well documented([1,2]). During the past 18 years, EU legislation has steadily been introduced to restrict its use, leaving a requirement for the development of replacement materials. This paper looks at possible alternatives to various cadmium II-VI dielectric compounds used in the deposition of optical thin-films for various opto-electronic devices. Application areas of particular interest are for infrared multilayer interference filter fabrication and solar cell industries, where cadmium-based coatings currently find widespread use. The results of single and multilayer designs comprising CdTe, CdS, CdSe and PbTe deposited onto group IV and II-VI materials as interference filters for the mid-IR region are presented. Thin films of SnN, SnO2, SnS and SnSe are fabricated by plasma assisted CVD, reactive RF sputtering and thermal evaporation. Examination of these films using FTIR spectroscopy, SEM, EDX analysis and optical characterisation methods provide details of material dispersion, absorption, composition, refractive index, energy band gap and layer thicknesses. The optimisation of deposition parameters in order to synthesise coatings with similar optical and semiconductor properties as those containing cadmium has been investigated. Results of environmental, durability and stability trials are also presented.

Neural and wavelet network models for financial distress classification

This work analyzes the use of linear discriminant models, multi-layer perceptron neural networks and wavelet networks for corporate financial distress prediction. Although simple and easy to interpret, linear models require statistical assumptions that may be unrealistic. Neural networks are able to discriminate patterns that are not linearly separable, but the large number of parameters involved in a neural model often causes generalization problems. Wavelet networks are classification models that implement nonlinear discriminant surfaces as the superposition of dilated and translated versions of a single "mother wavelet" function. In this paper, an algorithm is proposed to select dilation and translation parameters that yield a wavelet network classifier with good parsimony characteristics. The models are compared in a case study involving failed and continuing British firms in the period 1997-2000. Problems associated with over-parameterized neural networks are illustrated and the Optimal Brain Damage pruning technique is employed to obtain a parsimonious neural model. The results, supported by a re-sampling study, show that both neural and wavelet networks may be a valid alternative to classical linear discriminant models.

Comparison of extrasystolic ECG signal classifiers using discrete wavelet transforms

This work compares and contrasts results of classifying time-domain ECG signals with pathological conditions taken from the MITBIH arrhythmia database. Linear discriminant analysis and a multi-layer perceptron were used as classifiers. The neural network was trained by two different methods, namely back-propagation and a genetic algorithm. Converting the time-domain signal into the wavelet domain reduced the dimensionality of the problem at least 10-fold. This was achieved using wavelets from the db6 family as well as using adaptive wavelets generated using two different strategies. The wavelet transforms used in this study were limited to two decomposition levels. A neural network with evolved weights proved to be the best classifier with a maximum of 99.6% accuracy when optimised wavelet-transform ECG data wits presented to its input and 95.9% accuracy when the signals presented to its input were decomposed using db6 wavelets. The linear discriminant analysis achieved a maximum classification accuracy of 95.7% when presented with optimised and 95.5% with db6 wavelet coefficients. It is shown that the much simpler signal representation of a few wavelet coefficients obtained through an optimised discrete wavelet transform facilitates the classification of non-stationary time-variant signals task considerably. In addition, the results indicate that wavelet optimisation may improve the classification ability of a neural network. (c) 2005 Elsevier B.V. All rights reserved.