Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Simultaneous information and power transfer over the wireless channels potentially offers great convenience to mobile users. Yet practical receiver designs impose technical constraints on its hardware realization, as practical circuits for harvesting energy from radio signals are not yet able to decode the carried information directly. To make theoretical progress, we propose a general receiver operation, namely, dynamic power splitting (DPS), which splits the received signal with adjustable power ratio for energy harvesting and information decoding, separately. Three special cases of DPS, namely, time switching (TS), static power splitting (SPS) and on-off power splitting (OPS) are investigated. The TS and SPS schemes can be treated as special cases of OPS. Moreover, we propose two types of practical receiver architectures, namely, separated versus integrated information and energy receivers. The integrated receiver integrates the front-end components of the separated receiver, thus achieving a smaller form factor. The rate-energy tradeoff for the two architectures are characterized by a so-called rate-energy (R-E) region. The optimal transmission strategy is derived to achieve different rate-energy tradeoffs. With receiver circuit power consumption taken into account, it is shown that the OPS scheme is optimal for both receivers. For the ideal case when the receiver circuit does not consume power, the SPS scheme is optimal for both receivers. In addition, we study the performance for the two types of receivers under a realistic system setup that employs practical modulation. Our results provide useful insights to the optimal practical receiver design for simultaneous wireless information and power transfer (SWIPT).

Wireless Information and Power Transfer: Architecture Design and Rate-Energy Tradeoff

Fast Fourier Transform

Digital Coding of Waveforms

Most literature on support vector machines (SVMs) concentrates on the dual optimization problem. In this letter, we point out that the primal problem can also be solved efficiently for both linear and nonlinear SVMs and that there is no reason for ignoring this possibility. On the contrary, from the primal point of view, new families of algorithms for large-scale SVM training can be investigated.

/pdf/training-a-support-vector-machine-in-the-primal-35n02u1ajp.pdf

Training a Support Vector Machine in the Primal

Ultrasonic sensor measurements are mostly based on the determination of the time of flight (TOF). The authors present the development of a digital algorithm for pulse-echo measurement applications, based on the use of a cross-correlation function to determine the TOF. Some experimental results are presented, and the possibility of realizing a low-cost real-time measurement system is considered. >

Digital time-of-flight measurement for ultrasonic sensors

In this paper, we analyze the accuracy of indoor localization measurement based on a wireless sensor network. The position estimation procedure is based on the received-signal-strength measurements collected in a real indoor environment. Two different classes of low-computational-effort algorithms based on the centroid concept are considered, i.e., the weighted centroid localization method and the relative-span exponential weighted localization method. In particular, different sources of measurement uncertainty are analyzed by means of theoretical simulations and experimental results.

Accuracy of RSS-Based Centroid Localization Algorithms in an Indoor Environment

It is well-known that in discrete-Fourier-transform- (DFT-) based waveform analysis of multifrequency signals, spectral parameter accuracy can be increased by windowing the time samples and interpolating the DFT coefficients. It is shown that some relationships used in interpolation are affected very little by the number of processed samples, so that only the characteristics of the analyzed signal and the required accuracy affect the choice of this parameter. In particular, this makes the approach well suited for real-time analysis of signals with slowly time-varying spectra. Polynomial approximations of some relationships reduce the processing effort and, allow a greater freedom in the choice of the window functions, improving both accuracy and frequency resolution. >

Interpolation techniques for real-time multifrequency waveform analysis

The author investigates the influence of windowing on the accuracy of a frequency-domain procedure suitable for real-time estimations of multifrequency signal parameters. Imposing very weak assumptions about the statistical description of the noise, simple and accurate expressions for the estimator variances are established. They allow both the evaluation of the result accuracy and the design of the measurement procedure. Simulation results confirm the validity of the presented analysis. >

The influence of windowing on the accuracy of multifrequency signal parameter estimation

This paper investigates the accuracy of synchrophasor estimators provided by the interpolated discrete Fourier transform (IpDFT) algorithm under both steady-state and dynamic conditions when two- or three-cycle length observation intervals are considered. According to the IEEE Standard C37.118.1-2011 about synchrophasor measurements for power systems, the estimation accuracy is expressed by the total vector error (TVE). The effect on the estimation accuracy of different window functions, observation interval lengths, and processed DFT samples is analyzed through computer simulations. It is shown that most of the performance requirements specified in the Standard can be satisfied with a proper selection of the algorithm characteristics. Also, the performances of the proposed synchrophasor estimators and state-of-the-art estimators recently proposed in the scientific literature are compared and discussed. Some experimental results are presented in order to confirm the performed analysis.

Dario Petri

Papers

Digital time-of-flight measurement for ultrasonic sensors

Accuracy of RSS-Based Centroid Localization Algorithms in an Indoor Environment

Interpolation techniques for real-time multifrequency waveform analysis

The influence of windowing on the accuracy of multifrequency signal parameter estimation

Accuracy Analysis of the Multicycle Synchrophasor Estimator Provided by the Interpolated DFT Algorithm