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In this paper, two-parameter families of periodic current waveforms for class-F and inverse class-F power amplifiers (PAs) are considered. These waveforms are obtained by truncating cosine waveforms composed of dc component and fundamental and either second (k=2) or third (k=3) harmonic. In each period, waveforms are truncated to become zero outside of a prescribed interval (so-called conduction angle). The considered families of waveforms include both discontinuous and continuous waveforms. Fourier series expansion of truncated waveform contains an infinite number of harmonics, although a number of harmonics may be missing. Taking into account common assumptions that for class-F PA the third (n=3) harmonic is missing in current waveform and for inverse class-F PA the second (n=2) harmonic is missing in current waveform, we consider the following four cases: (i) n=k=3, (ii) n=3, k=2, (iii) n=k=2, and (iv) n=2, k=3. We show that, in each of these cases, current waveform enabling maximal efficiency (optimal waveform) of class-F and inverse class-F PA is continuous for all conduction angles of practical interest. Furthermore, we provide closed-form expressions for parameters of optimal current waveforms and maximal efficiency of class-F (inverse class-F) PA in terms of conduction angle only. Two case studies of practical interest for PA design, involving suboptimal current waveforms, along with the results of nonlinear simulation of inverse class-F PA, are also presented. [ABSTRACT FROM AUTHOR]

This paper proposes universal coarse-grained reconfigurable computing architecture for hardware implementation of decision trees (DTs), artificial neural networks (ANNs), and support vector machines (SVMs), suitable for both field programmable gate arrays (FPGA) and application specific integrated circuits (ASICs) implementation. Using this universal architecture, two versions of DTs (functional DT and axis-parallel DT), two versions of SVMs (with polynomial and radial kernel) and two versions of ANNs (multi layer perceptron ANN and radial basis ANN) machine learning classifiers, have been implemented in FPGA. Experimental results, based on 18 benchmark datasets of standard UCI machine learning repository database, show that FPGA implementation provides significant improvement (1-2 orders of magnitude) in the average instance classification time, in comparison with software implementations based on R project. [ABSTRACT FROM AUTHOR]

Various classes of nonnegative waveforms containing dc component, fundamental and kth harmonic k≥2, which proved to be of interest in waveform modelling for power amplifier (PA) design, are considered in this paper. In optimization of PA efficiency, nonnegative waveforms with maximal amplitude of fundamental harmonic and those with maximal coefficient of cosine term of fundamental harmonic (optimal waveforms) play an important role. Optimal waveforms have multiple global minima and this fact closely relates the problem of optimization of PA efficiency to the concept of conflict set. There is also keen interest in finding descriptions for various classes of suboptimal waveforms, such as nonnegative waveforms with at least one zero, nonnegative waveforms with maximal amplitude of fundamental harmonic for prescribed amplitude of kth harmonic, nonnegative waveforms with maximal coefficient of cosine part of fundamental harmonic for prescribed coefficients of kth harmonic, and nonnegative cosine waveforms with at least one zero. Closed form descriptions for all these suboptimal types of waveforms are provided in this paper. Suboptimal waveforms may also have multiple global minima and therefore be related to the concept of conflict set. Four case studies of usage of closed form descriptions of nonnegative waveforms in PA modelling are also provided. [ABSTRACT FROM AUTHOR]

General description of nonnegative waveforms up to second harmonic in terms of independent (unconstrained) parameters is provided. Three important subclasses of the class of nonnegative waveforms are also fully characterised: nonnegative waveforms with maximal amplitude of fundamental harmonic for prescribed amplitude of second harmonic, nonnegative waveforms with maximal coefficient of cosine part of fundamental harmonic for prescribed coefficients of second harmonic, and nonnegative waveforms with at least one zero. We prove that members of the first two subclasses have at least one zero; that is, they also belong to the third subclass. Nonnegative cosine waveforms up to second harmonic are also considered and characterised. A number of case studies of practical interest for power amplifier (PA) design, involving nonnegative waveforms up to second harmonic, are also considered. [ABSTRACT FROM AUTHOR]

In this paper, several hardware architectures for the realization of ensembles of axis-parallel, oblique and nonlinear decision trees (DTs) are presented. Hardware architectures for the implementation of a number of ensemble combination rules are also presented. These architectures are universal and can be used to combine predictions from any type of classifiers, such as decision trees, artificial neural networks (ANNs) and support vector machines (SVMs). Proposed architectures are suitable for the implementation using Field Programmable Gate Arrays (FPGA) and Application Specific Integrated Circuits (ASIC). Experiment results obtained using 29 datasets from the standard UCI Machine Learning Repository database suggest that the FPGA implementations offer significant improvement in the classification time in comparison with the traditional software implementations. Greatest improvement can be achieved using the SP2-P architecture implemented on the FPGA achieving 416.53 times faster classification speed on average, compared with the software implementation. This result has been achieved on the FPGA working at 135.51 MHz on average, which is 33.21 times slower than the operating frequency of the general purpose computer on which the software implementation has been executed. [ABSTRACT FROM AUTHOR]

In this paper general solution to the problem of finding maximally flat waveforms with finite number of harmonics (maximally flat trigonometric polynomials) is provided. Waveform coefficients are expressed in closed form as functions of harmonic orders. Two special cases of maximally flat waveforms (so-called maximally flat even harmonic and maximally flat odd harmonic waveforms), which proved to play an important role in class-F and inverse class-F power amplifier (PA) operations, are also considered. For these two special types of waveforms, coefficients are expressed as functions of two parameters only. Closed form expressions for efficiency and power output capability of class-F and inverse class-F PA operations with maximally flat waveforms are also provided as explicit functions of number of a harmonics. [ABSTRACT FROM AUTHOR]

The influence of cryo-treatment is investigated according to some magnetic and thermal properties of Fe40 Ni40 Si6 B14 glassy alloy. Saturation magnetization (MS), amorphous Curie temperature (TCam) heat capacity (Cr) and the width of crystallization exotherm peak were measured before and after the cryo-treatment. The treatment causes a very stable structural imprint in the investigated properties. Not all property changes are completely irreversible, however. The TCam exhibits a very slow, viscous reconstruction during subsequent isothermal or cyclic heat treatments. The heat capacity of cryo-treated samples increases compared to the nontreated ones. Due to the low temperature treatment the kinetic of crystallization changes also, which is manifested in the shift of half width of crystallization peak. The magnitude of the LN treatment induced effects depends on the whole thermal history of the sample. [ABSTRACT FROM AUTHOR]

This paper, according to the best of our knowledge, provides the very first solution to the hardware implementation of the complete decision tree inference algorithm. Evolving decision trees in hardware is motivated by a significant improvement in the evolution time compared to the time needed for software evolution and efficient use of decision trees in various embedded applications (robotic navigation systems, image processing systems, etc.), where run-time adaptive learning is of particular interest. Several architectures for the hardware evolution of single oblique or nonlinear decision trees and ensembles comprised from oblique or nonlinear decision trees are presented. Proposed architectures are suitable for the implementation using both Field Programmable Gate Arrays (FPGA) and Application Specific Integrated Circuits (ASIC). Results of experiments obtained using 29 datasets from the standard UCI Machine Learning Repository database suggest that the FPGA implementations offer significant improvement in inference time when compared with the traditional software implementations. In the case of single decision tree evolution, FPGA implementation of H_DTS2 architecture has on average 26 times shorter inference time when compared to the software implementation, whereas FPGA implementation of H_DTE2 architecture has on average 693 times shorter inference time than the software implementation. [ABSTRACT FROM AUTHOR]

Presents a balance power analysis of high frequency high powered tuned amplifier (HFHPTA) with composite drive and output signal obtained by injection of two harmonics. Simplified model of HFHPTA with injection of two harmonics; Results of general balance power analysis of HFHPTA.

Presents a complete account of composite periodic signals with two and three harmonics including their application in the balance power analysis of high frequency high-power tuned amplifiers (HFHPTA). Simplified model of an HFHPTA with injected N-harmonic signal into an M-harmonic carrier; Flattened extrema of composite periodic signal with two harmonics.

Presents general balance power analysis of HF high-power tuned amplifiers with composite drive and output signal obtained by injection of an N-harmonic signal into M-harmonic carrier signal. Flattened extremums; Composite periodic signals with two harmonics.

Hense H-W (GSF Research Center for Environment and Health, Institute of Epidemiology, Ingolstaedter Landstr.1, D-8042 Neuherberg, Germany), Filipiak B, Novak L and Stoeppler M. Nonoccupational determinants of blood lead concentrations in a general population. International Journal of Epidemiology 1992; 2l: 753–762.We investigated the influence of various nonoccupational factors on blood lead levels (PbB) in a sample from the general population of southern Germany. Some 1703 men and 1661 women, aged 28–67 years, were examined in the first follow-up examination of the MONICA Augsburg cohort study in 1587–1988. Their mean PbB was 90 mg/I (SD: 35.9) for men and 65 mg/I (26.4) for women. Only 5% of the men and 1% of all women exceeded a PbB level of 150 mg/I indicating low-level lead exposure in this population. Blood lead was significantly associated with haematocrit values (P'0.0011 and the shape of this association was curvilinear. Per gram of alcohol consumed, intake of beer had a lower impact on PbB than wine, presumably due to differential lead content in these alcoholic beverages. The alcohol-PbB associations were stronger for women than for men. The impact of smoking was generally moderate but again more prominent in women. In particular, the covariate adjusted odds ratios for women of childbearing age (28–47 years) to have PbB levels above 100 mg/I were 2.5 (95% confidence interval (CI): 1.3–4.7) for smoking versus nonsmoking females, 2.6 (95% CI: 1.1–6.0) for women drinking up to 40 g alcohol/day compared to abstainers, and 8.9 (95% CI: 3.2–25.1) for those drinking more than 40 g alcohol/day. Other factors like age, body mass, rural place of residence, and education or job position, had only minor influences on PbB. We conclude that haematocrit values should always be considered as potential confounders in low-level lead exposure research. High alcohol consumption and cigarette smoking are strongly related to elevated blood lead concentrations in the general population and may thereby convey additional health hazards such as impaired child development or blood pressure elevations. This deserves proper public health recognition. [ABSTRACT FROM PUBLISHER]

Deals with a study which measured the amount of total body water and solids in a sample of normal children of both sexes. Subjects and methods; Values for total body water and solids; Sex differences in total body water and solids.