Combining the wavelet transform and forecasting models to predict gas forward prices

This paper presents a forecasting technique for forward energy prices, one day ahead. This technique combines a wavelet transform and forecasting models such as multi- layer perceptron, linear regression or GARCH. These techniques are applied to real data from the UK gas markets to evaluate their performance. The results show that the forecasting accuracy is improved significantly by using the wavelet transform. The methodology can be also applied to forecasting market clearing prices and electricity/gas loads.

A generative probabilistic oriented wavelet model for texture segmentation

This Letter addresses image segmentation via a generative model approach. A Bayesian network (BNT) in the space of dyadic wavelet transform coefficients is introduced to model texture images. The model is similar to a Hidden Markov model (HMM), but with non-stationary transitive conditional probability distributions. It is composed of discrete hidden variables and observable Gaussian outputs for wavelet coefficients. In particular, the Gabor wavelet transform is considered. The introduced model is compared with the simplest joint Gaussian probabilistic model for Gabor wavelet coefficients for several textures from the Brodatz album [1]. The comparison is based on cross-validation and includes probabilistic model ensembles instead of single models. In addition, the robustness of the models to cope with additive Gaussian noise is investigated. We further study the feasibility of the introduced generative model for image segmentation in the novelty detection framework [2]. Two examples are considered: (i) sea surface pollution detection from intensity images and (ii) image segmentation of the still images with varying illumination across the scene.

Turbulent broadening of optical spectra in ultralong Raman fiber lasers

We study the properties of radiation generated in ultralong fiber lasers and find an interesting link between these optical systems and the theory of weak wave turbulence. Experimental observations strongly suggest that turbulentlike weak interactions between the multitude of laser cavity modes are responsible for practical characteristics of ultralong fiber lasers such as spectra of the output radiation.

The vibrational spectra of rectangular plates

The wire drive pulse-echo system has been extensively used to excite and measure modes of vibration of thin rectangular plates. The frequency spectra of different modes have been investigated as a function of the material elastic moduli and the plate geometry. Most of the work was carried out on isotropic materials. For square plates a wide selection of materials were used. These were made isotropic in their in-plane dimensions where the displacements are taking place. The range of rnaterials enabled the dependence on Poisson's ratio to be investigated. A method of determining the value of Poisson's ratio resulted from this investigation. Certain modes are controlled principally by the shear modulus. Of these the fundamental has two nodal lines across the plate surface. One of them, which has nodes at the corners, (the Lame mode) is uniquely a pure shear mode where the diagonal is a full wave length. One controlled by the Young's modulus has been found. The precise harmonic relationship of the Lame mode series in square and rectangular plates was established. Use of the Rayleigh-Lamb equation has extended the theoretical support. The low order modes were followed over a wide range of sides ratios. Two fundamental types of modes have been recognised; These are the longitudinal modes where the frequency is controlled by the length of the plate only and the 2~f product has an asymptotic value approaching the rod velocity. The other type is the in-plane flexural modes (in effect a flexurally vibrating bar where the -2/w is the geometrical parameter). Where possible the experimental work was related to theory. Other modes controlled by the width dimension of the plate were followed. Anisotropic materials having rolled sheet elastic symmetry were investigated in terms of the appropriate theory. The work has been extended to examine materials from welds in steel plates.

Evaluation of the sonically induced narrowing of nuclear magnetic resonance spectra of solids

The Nuclear Magnetic Resonance (NMR) spectra of liquids contain a wealth of quantitative information that may be derived, for instance, from chemical shifts and spin-spin couplings. The available information depends on the incoherent rapid molecular motion that causes complicating effects present in the solid state to average to zero. Whereas liquid state NMR spectra show narrow lines, the corresponding NMR spectra from the solid state are normally composed of exceedingly broad resonance lines due to highly restricted molecular motion. It is, therefore, difficult to obtain directly as detailed information from the spectra of solids as from those derived from the liquid state. Studies on a new technique (SINNMR, the sonically induced narrowing of the NMR spectra of solids) to remove line broadening effects in the NMR spectra of the solid state are reported within this thesis. SINNMR involves narrowing the NMR absorptions from solid particles by irradiating them with ultrasound when they are suspended in a support liquid. It is proposed that ultrasound induces incoherent motion of the suspended particles, producing motional characteristics of the particles similar to those of rather large molecules. The first report of apparently successful experiments involving SINNMR[1] emphasised both the irreproducibility of the technique and the uncertainty regarding its true origin. If SINNMR can be made reproducible and the effect definitively attributed to the sonically induced incoherent motional averaging of particles, the technique could offer a simple alternative to the now classical magic-angle spinning (MAS) NMR[2] and the recently reported dynamic angle spinning (DAS)[3] and double rotation (DOR)[4] techniques. Evidence is presented in this thesis to support the proposal that ultrasound may be used to narrow the NMR spectral resonances from solids by inducing incoherent motion of particles suspended in support liquids and, additionally, for some solids, by inducing rotational motion of molecular constituents in the lattices of solids. Successful SINNMR line narrowing using 20 kHz ultrasound is reported for a variety of samples: including trisodium orthophosphate, polytetrafluoroethylene and aluminium alloys. Investigations of SINNMR line narrowing in trisodium phosphate have revealed the relationship between ultrasonic power, particle size and support liquid density for the production of optimum SINNMR conditions. It is also proposed that the incoherent motion of particles induced by 20 kHz ultrasound can originate from interactions between acoustically induced cavitation microjets and particles.

Sonically induced narrowing of the NMR spectra of solids and other novel NMR techniques

A typical liquid state NMR spectrum is composed of a number of discrete absorptions which can be readily interpreted to yield detailed information about the chemical environment of the nuclei found within the sample. The same cannot be said about the spectra of solid samples. For these the absorptions are typically broad, featureless and yield little information directly. This situation may be further exacerbated by the characteristically long T1 values of nuclei bound within a solid lattice which, consequently, require long inter-sequence delays that necessitate lengthy experiments. This work attempts to address both of these inherent problems. Classically, the resolution of the broad-line spectra of solids into discrete resonances has been achieved by imparting to the sample coherent rotation about specific axes in relation to the polarising magnetic field, as implemented in the magic-angle spinning (MAS) [1], dynamic angle spinning (DAS) [2] and double rotation (DOR) [3] NMR experiments. Recently, an alternative method, sonically induced narrowing of the NMR spectra of solids (SINNMR) [4], has been reported which yields the same well resolved solid-state spectra as the classic solid-state NMR experiments, but which achieves the resolution of the broad-line spectra through the promotion of incoherent motion in a suspension of solid particles. The first part of this work examines SINNMR and, in particular, concentrates on ultrasonically induced evaluation, a phenomenon which is thought to be essential to the incoherent averaging mechanism. The second part of this work extends the principle of incoherent motion, implicit in SINNMR, to a new genre of particulate systems, air fluidized beds, and examines the feasibility of such systems to provide well resolved solid state NMR spectra. Samples of trisodium phosphate dodecahydrate and of aluminium granules are examined using the new method with partially resolved spectra being reported in the case of the latter.

Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models

This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH). To create an adaptive model, we use an extended Kalman filter or particle filter to update the parameters continuously on the test set. The adaptive GARCH model is a new contribution, broadening the applicability of GARCH methods. We empirically compared two approaches of combining the WT with prediction models: multicomponent forecasts and direct forecasts. These techniques are applied to large sets of real data (both stationary and non-stationary) from the UK energy markets, so as to provide comparative results that are statistically stronger than those previously reported. The results showed that the forecasting accuracy is significantly improved by using the WT and adaptive models. The best models on the electricity demand/gas price forecast are the adaptive MLP/GARCH with the multicomponent forecast; their MSEs are 0.02314 and 0.15384 respectively.

Characterizing femtosecond laser inscribed Bragg grating spectra

We present numerical modeling based on a combination of the Bidirectional Beam Propagation Method and Finite Element Method that completely describes the wavelength spectra of point by point femtosecond laser inscribed fiber Bragg gratings, showing excellent agreement with experiment. We have investigated the dependence of different spectral parameters such as insertion loss, all dominant cladding and ghost modes and their shape relative to the position of the fiber Bragg grating in the core of the fiber. Our model is validated by comparing model predictions with experimental data and allows for predictive modeling of the gratings. We expand our analysis to more complicated structures, where we introduce symmetry breaking; this highlights the importance of centered gratings and how maintaining symmetry contributes to the overall spectral quality of the inscribed Bragg gratings. Finally, the numerical modeling is applied to superstructure gratings and a comparison with experimental results reveals a capability for dealing with complex grating structures that can be designed with particular wavelength characteristics. (C) 2010 Optical Society of America

From cardinal spline wavelet bases to highly coherent dictionaries

Wavelet families arise by scaling and translations of a prototype function, called the mother wavelet. The construction of wavelet bases for cardinal spline spaces is generally carried out within the multi-resolution analysis scheme. Thus, the usual way of increasing the dimension of the multi-resolution subspaces is by augmenting the scaling factor. We show here that, when working on a compact interval, the identical effect can be achieved without changing the wavelet scale but reducing the translation parameter. By such a procedure we generate a redundant frame, called a dictionary, spanning the same spaces as a wavelet basis but with wavelets of broader support. We characterize the correlation of the dictionary elements by measuring their 'coherence' and produce examples illustrating the relevance of highly coherent dictionaries to problems of sparse signal representation.

Spectra of modular and small-world matrices

We compute spectra of symmetric random matrices describing graphs with general modular structure and arbitrary inter- and intra-module degree distributions, subject only to the constraint of finite mean connectivities. We also evaluate spectra of a certain class of small-world matrices generated from random graphs by introducing shortcuts via additional random connectivity components. Both adjacency matrices and the associated graph Laplacians are investigated. For the Laplacians, we find Lifshitz-type singular behaviour of the spectral density in a localized region of small |?| values. In the case of modular networks, we can identify contributions of local densities of state from individual modules. For small-world networks, we find that the introduction of short cuts can lead to the creation of satellite bands outside the central band of extended states, exhibiting only localized states in the band gaps. Results for the ensemble in the thermodynamic limit are in excellent agreement with those obtained via a cavity approach for large finite single instances, and with direct diagonalization results.

Impact of FBGs reflectivity shape on spectra of radiation in 10 km Raman fibre laser

We study the impact of the shape of fibre Bragg gratings spectral reflectivity on spectral broadening in a 10 km Raman fibre laser. We show that, at high powers, spectral characteristics are determined by intra-cavity processes rather than by the gratings profile.