Learning from time series:Supervised Aggregative Feature Extraction

Many modeling problems require to estimate a scalar output from one or more time series. Such problems are usually tackled by extracting a fixed number of features from the time series (like their statistical moments), with a consequent loss in information that leads to suboptimal predictive models. Moreover, feature extraction techniques usually make assumptions that are not met by real world settings (e.g. uniformly sampled time series of constant length), and fail to deliver a thorough methodology to deal with noisy data. In this paper a methodology based on functional learning is proposed to overcome the aforementioned problems; the proposed Supervised Aggregative Feature Extraction (SAFE) approach allows to derive continuous, smooth estimates of time series data (yielding aggregate local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The SAFE paradigm enjoys several properties like closed form solution, incorporation of first and second order derivative information into the regressor matrix, interpretability of the generated functional predictor and the possibility to exploit Reproducing Kernel Hilbert Spaces setting to yield nonlinear predictive models. Simulation studies are provided to highlight the strengths of the new methodology w.r.t. standard unsupervised feature selection approaches. © 2012 IEEE.

Supervised Aggregative Feature Extraction for Big Data Time Series Regression

In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.

Exploring figures of merit associated with the suboptimum operation of class-E power amplifiers

Closed-form design equations for the operation of a class-E amplifier for zero switch voltage slope and arbitrary duty cycle are derived. This approach allows an additional degree of freedom in the design of class-E amplifiers which are normally designed for 50 duty ratio. The analysis developed permits the selection of non-unique solutions where amplifier efficiency is theoretically 100 but power output capability is less than that the 50 duty ratio case would permit. To facilitate comparison between 50 (optimal) and non-50 (suboptimal) duty ratio cases, each important amplifier parameter is normalised to its corresponding optimum operation value. It is shown that by choosing a non-50 suboptimal solution, the operating frequency of a class-E amplifier can be extended. In addition, it is shown that by operating the amplifier in the suboptimal regime, other amplifier parameters, for example, transistor output capacitance or peak switch voltage, can be included along with the standard specification criteria of output power, DC supply voltage and operating frequency as additional input design specifications. Suboptimum class-E operation may have potential advantages for monolithic microwave integrated circuit realisation as lower inductance values (lower series resistance, higher self-resonance frequency, less area) may be required when compared with the results obtained for optimal class-E amplifier synthesis. The theoretical analysis conducted here was verified by harmonic balance simulation, with excellent agreement between both methods. © The Institution of Engineering and Technology 2007.

Threshold-based substream selection for closed-loop spatial multiplexing

We propose a low-complexity closed-loop spatial multiplexing method with limited feedback over multi-input-multi-output (MIMO) fading channels. The transmit adaptation is simply performed by selecting transmit antennas (or substreams) by comparing their signal-to-noise ratios to a given threshold with a fixed nonadaptive constellation and fixed transmit power per substream. We analyze the performance of the proposed system by deriving closed-form expressions for spectral efficiency, average transmit power, and bit error rate (BER). Depending on practical system design constraints, the threshold is chosen to maximize the spectral efficiency (or minimize the average BER) subject to average transmit power and average BER (or spectral efficiency) constraints, respectively. We present numerical and Monte Carlo simulation results that validate our analysis. Compared to open-loop spatial multiplexing and other approaches that select the best antenna subset in spatial multiplexing, the numerical results illustrate that the proposed technique obtains significant power gains for the same BER and spectral efficiency. We also provide numerical results that show improvement over rate-adaptive orthogonal space-time block coding, which requires highly complex constellation adaptation. We analyze the impact of feedback delay using analytical and Monte Carlo approaches. The proposed approach is arguably the simplest possible adaptive spatial multiplexing system from an implementation point of view. However, our approach and analysis can be extended to other systems using multiple constellations and power levels.

Multiuser Cognitive Relay Networks: Joint Impact of Direct and Relay Communications

In this paper, we propose a multiuser cognitive relay network, where multiple secondary sources communicate with a secondary destination through the assistance of a secondary relay in the presence of secondary direct links and multiple primary receivers. We consider the two relaying protocols of amplify-and-forward (AF) and decode-and-forward (DF), and take into account the availability of direct links from the secondary sources to the secondary destination. With this in mind, we propose an optimal solution for cognitive multiuser scheduling by selecting the optimal secondary source, which maximizes the received signal-to-noise ratio (SNR) at the secondary destination using maximal ratio combining. This is done by taking into account both the direct link and the relay link in the multiuser selection criterion. For both AF and DF relaying protocols, we first derive closed-form expressions for the outage probability and then provide the asymptotic outage probability, which determines the diversity behavior of the multiuser cognitive relay network. Finally, this paper is corroborated by representative numerical examples.

Improved model for interfacial stresses accounting for the effect of shear deformation in plated beams

A significant increase in strength and performance of reinforced concrete, timber and metal beams may be achieved by adhesively bonding a fibre reinforced polymer composite, or metallic such as steel plate to the tension face of a beam. One of the major failure modes in these plated beams is the debonding of the plate from the original beam in a brittle manner. This is commonly attributed to the interfacial stresses between the adherends whose quantification has led to the development of many analytical solutions over the last two decades. The adherends are subjected to axial, bending and shear deformations. However, most analytical solutions have neglected the effect of shear deformation in adherends. Few solutions consider this effect approximately but are limited to one or two specific loading conditions. This paper presents a more rigorous solution for interfacial stresses in plated beams under an arbitrary loading with the shear deformation of the adherends duly considered in closed form using Timoshenko’s beam theory. The solution is general to linear elastic analysis of prismatic beams of arbitrary cross section under arbitrary loading with a plate of any thickness bonded either symmetrically or asymmetrically with respect to the span of the beam.

Nonlinear response of permanent dipoles in a uniaxial potential to alternating fields

It is shown how the existing theory of the dynamic Kerr effect and nonlinear dielectric relaxation based on the noninertial Brownian rotation of noninteracting rigid dipolar particles may be generalized to take into account interparticle interactions using the Maier-Saupe mean field potential. The results (available in simple closed form) suggest that the frequency dependent nonlinear response provides a method of measuring the Kramers escape rate (or in the analogous problem of magnetic relaxation of fine single domain ferromagnetic particles, the superparamagnetic relaxation time).

Spatially Correlated Multiple-Ananna Channel Capacity Distributions

In this paper, we investigate the capacity of multiple-input multiple-output (MIMO) wireless communication systems over spatially correlated Rayleigh distributed flat fading channels with complex Gaussian additive noise. Specifically, we derive the probability density function of the mutual information between transmitted and received complex signals of MIMO systems. Using this density we derive the closed-form ergodic capacity (mean), delay-limited capacity, capacity variance and outage capacity formulas for spatially correlated channels and then evaluate these formulas numerically. Numerical results show how the channel correlation degrades the capacity of MIMO communication systems. We also show that the density of mutual information of correlated/uncorrelated MIMO systems can be approximated by a Gaussian density with derived mean and variance, even for a finite number of inputs and outputs.

Higher order statistics for the κ–μ distribution

Closed-form expressions for the level crossing rate and average fade duration of a kappa–mu distributed fading signal envelope are presented. The proposed equations are validated by reduction to known Rice, Rayleigh and Nakagami-m special cases. They are also compared with measured data obtained from field trials analysing human body to body radio channels and shown to provide good agreement.

An efficient method of radiation attenuation through aircraft cooling vents

Some critical avionic systems require cooling air via vents on the side of the aircraft, thus creating leakage points for high-intensity electromagnetic radiation. This paper presents a novel application of high-intensity radiated field (HIRF) shielding using a rectangular waveguide array, while maintaining cooling airflow requirements. Signal attenuation versus frequency and depth of the array has been calculated using closed-form equations. The simulation and measurement results are in good agreement with the calculated values. (C) 2004 Wiley Periodicals, Inc.

Analysis of the effect of finite d.c. blocking capacitance and finite d.c. feed inductance on the performance of inverse class-E amplifiers

The first analysis and synthesis equations for the newly introduced inverse Class-E amplifier when operated with a finite d.c. blocking capacitance and a finite d.c.-feed inductance are presented in the paper. Closed-form design equations are derived in order to establish the circuit component values required for optimum synthesis. Excellent agreement between numerical simulation results and theoretical prediction is obtained. It is shown that drain efficiency approaching 100 at a pre-specified output power level can be achieved as zero-current switching and zero-current derivative conditions are simultaneously satisfied. The proposed analysis offers the prospect for realistic MMIC implementation.

Series-L/parallel-tuned comparison with shunt-C/series-tuned class-E power amplifier

An analysis of the operation of a series-L/parallel-tuned class-E amplifier and its equivalence to the classic shunt-C/series-tuned class-E amplifier are presented. The first reported closed form design equations for the series-L/parallel-tuned topology operating under ideal switching conditions are given. Furthermore, a design procedure is introduced that allows the effect that nonzero switch resistance has on amplifier performance efficiency to be accounted for. The technique developed allows optimal circuit components to be found for a given device series resistance. For a relatively high value of switching device ON series resistance of 4O, drain efficiency of around 66% for the series-L/parallel-tuned topology, and 73% for the shunt-C/series-tuned topology appear to be the theoretical limits. At lower switching device series resistance levels, the efficiency performance of each type are similar, but the series-L/parallel-tuned topology offers some advantages in terms of its potential for MMIC realisation. Theoretical analysis is confirmed by numerical simulation for a 500mW (27dBm), 10% bandwidth, 5 V series-L/parallel-tuned, then, shunt-C/series-tuned class E power amplifier, operating at 2.5 GHz, and excellent agreement between theory and simulation results is achieved. The theoretical work presented in the paper should facilitate the design of high-efficiency switched amplifiers at frequencies commensurate with the needs of modern mobile wireless applications in the microwave frequency range, where intrinsically low-output-capacitance MMIC switching devices such as pHEMTs are to be used.

A self-structured adaptive decision feedback equalizer

In a decision feedback equalizer (DFE), the structural parameters, including the decision delay, the feedforward filter (FFF), and feedback filter (FBF) lengths, must be carefully chosen, as they greatly influence the performance. Although the FBF length can be set as the channel memory, there is no closed-form expression for the FFF length and decision delay. In this letter, first we analytically show that the two-dimensional search for the optimum FFF length and decision delay can be simplified to a one-dimensional search and then describe a new adaptive DFE where the optimum structural parameters can he self-adapted.