Combining Mager and Steinmetz: The Effect of Grain Size and Maximum Induction on Hysteresis Energy Loss

Twelve samples with different grain sizes were prepared by normal grain growth and by primary recrystallization, and the hysteresis dissipated energy was measured by a quasi-static method. Results showed a linear relation between hysteresis energy loss and the inverse of grain size, which is here called Mager`s law, for maximum inductions from 0.6 to 1.5 T, and a Steinmetz power law relation between hysteresis loss and maximum induction for all samples. The combined effect is better described by a Mager`s law where the coefficients follow Steinmetz law.

Modeling of Plastic Deformation Effects in Ferromagnetic Thin Films

To explain the magnetic behavior of plastic deformation of thin magnetic films (Fe and permalloy) on an elastic substrate (nitinol), it is noted that unlike in the bulk, the dislocation density does not increase dramatically because of the dimensional constraint. As a result, the resulting residual stress, even though strain hardening is limited, dominates the observed magnetic behavior. Thus, with the field parallel to the stress axis, the compressive residual stress resulting from plastic deformation causes a decrease in remanence and an increase in coercivity; and with the field perpendicular to the stress axis, the resulting compressive residual stress causes an increase in remanence and a decrease in coercivity. These elements have been inserted into the model previously developed for plastic deformation in the bulk, producing the aforementioned behavior, which has been observed experimentally in the films.

Modeling of Effect of Plastic Deformation on Barkhausen Noise and Magnetoacoustic Emission in Iron With 2% Silicon

Before one models the effect of plastic deformation on magnetoacoustic emission (MAE), one must first treat non-180 degrees domain wall motion. In this paper, we take the Alessandro-Beatrice-Bertotti-Montorsi (ABBM) model and modify it to treat non-180 degrees wall motion. We then insert a modified stress-dependent Jiles-Atherton model, which treats plastic deformation, into the modified ABBM model to treat MAE and magnetic Barkhausen noise (HBN). In fitting the dependence of these quantities on plastic deformation, we apply a model for when deformation gets into the stage where dislocation tangles are formed, noting two chief effects, one due to increased density of emission centers owing to increased dislocation density, and the other due to a more gentle increase in the residual stress in the vicinity of the dislocation tangles as deformation is increased.

An In-Depth Study of the Barkhausen Emission Signal Properties of the Plastically Deformed Fe-2%Si Alloy

This paper presents the results of the in-depth study of the Barkhausen effect signal properties for the plastically deformed Fe-2%Si samples. The investigated samples have been deformed by cold rolling up to plastic strain epsilon(p) = 8%. The first approach consisted of time-domain-resolved pulse and frequency analysis of the Barkhausen noise signals whereas the complementary study consisted of the time-resolved pulse count analysis as well as a total pulse count. The latter included determination of time distribution of pulses for different threshold voltage levels as well as the total pulse count as a function of both the amplitude and the duration time of the pulses. The obtained results suggest that the observed increase in the Barkhausen noise signal intensity as a function of deformation level is mainly due to the increase in the number of bigger pulses.

An Array Recursive Least-Squares Algorithm With Generic Nonfading Regularization Matrix

We present a novel array RLS algorithm with forgetting factor that circumvents the problem of fading regularization, inherent to the standard exponentially-weighted RLS, by allowing for time-varying regularization matrices with generic structure. Simulations in finite precision show the algorithm`s superiority as compared to alternative algorithms in the context of adaptive beamforming.

Analysis of a Reconfigurable Bandpass Circular Patch Filter

This paper presents an analysis of a reconfigurable patch filter based on a triple-mode circular patch resonator with four radial slots. The analysis has been carried out thanks to the development of a new theoretical approach of the tunable patch filter based on the coupling matrix. The coefficients of the coupling matrix related to the tunable behavior have been identified and some rules for their evolution have been derived. For a proof-of-concept, a bandpass filter has been designed with a continuous tunability obtained with varactors connected across the slots. State-of-the-art results have been obtained, with a frequency tuning range of 27% from 1.95 to 2.43 GHz and a change in fractional bandwidth from 8.5% to 31.5% for the respective frequencies. In the entire tuning range, the return loss is better than 10 dB and the maximum insertion loss is 2 dB. Due to the newly developed coupling matrix, measurements, simulations, and theory showed great agreement.

Harmonic Distortion of Unstrained and Strained FinFETs Operating in Saturation

The harmonic distortion (HD) exhibited by un-strained and biaxially strained fin-shaped field-effect transistors operating in saturation as single-transistor amplifiers has been investigated for devices with different channel lengths L and fin widths W(fin). The study has been performed through device characterization, 3-D device simulations, and modeling. Nonlinearity has been evaluated in terms of second- and third-order HDs (HD2 and HD3, respectively), and a discussion on its physical sources has been carried out. Also, the influence of the open-loop voltage gain AV in HD has been observed.

Signals in Communication Engineering History

This paper is a study of various electric signals, which have been employed throughout the history of communication engineering in its two main landmarks: the telegraph and the telephone. The signals are presented in their time and frequency domain representations. The historical order has been followed in the presentation: wired systems, spark gap wireless, continuous wave (CW) and amplitude modulation (AM), detection by rectification, and frequency modulation (FM). The analysis of these signals is meant to lead into a better understanding of the evolution of communication technology. The material presented in this work could be used to illustrate ""Signals and Systems"" and ""Communication Systems"" courses by taking advantage of its technical as well as historical contents.

Adaptive Carrier Tracking for Mars to Earth Communications During Entry, Descent, and Landing

We propose a robust and low complexity scheme to estimate and track carrier frequency from signals traveling under low signal-to-noise ratio (SNR) conditions in highly nonstationary channels. These scenarios arise in planetary exploration missions subject to high dynamics, such as the Mars exploration rover missions. The method comprises a bank of adaptive linear predictors (ALP) supervised by a convex combiner that dynamically aggregates the individual predictors. The adaptive combination is able to outperform the best individual estimator in the set, which leads to a universal scheme for frequency estimation and tracking. A simple technique for bias compensation considerably improves the ALP performance. It is also shown that retrieval of frequency content by a fast Fourier transform (FFT)-search method, instead of only inspecting the angle of a particular root of the error predictor filter, enhances performance, particularly at very low SNR levels. Simple techniques that enforce frequency continuity improve further the overall performance. In summary we illustrate by extensive simulations that adaptive linear prediction methods render a robust and competitive frequency tracking technique.

Transient and Steady-State Analysis of the Affine Combination of Two Adaptive Filters

In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance. Good agreement between analysis and simulation results is always observed.

Fast Transforms for Acoustic Imaging-Part I: Theory

The classical approach for acoustic imaging consists of beamforming, and produces the source distribution of interest convolved with the array point spread function. This convolution smears the image of interest, significantly reducing its effective resolution. Deconvolution methods have been proposed to enhance acoustic images and have produced significant improvements. Other proposals involve covariance fitting techniques, which avoid deconvolution altogether. However, in their traditional presentation, these enhanced reconstruction methods have very high computational costs, mostly because they have no means of efficiently transforming back and forth between a hypothetical image and the measured data. In this paper, we propose the Kronecker Array Transform ( KAT), a fast separable transform for array imaging applications. Under the assumption of a separable array, it enables the acceleration of imaging techniques by several orders of magnitude with respect to the fastest previously available methods, and enables the use of state-of-the-art regularized least-squares solvers. Using the KAT, one can reconstruct images with higher resolutions than was previously possible and use more accurate reconstruction techniques, opening new and exciting possibilities for acoustic imaging.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

Fast Transforms for Acoustic Imaging-Part II: Applications

In Part I [""Fast Transforms for Acoustic Imaging-Part I: Theory,"" IEEE TRANSACTIONS ON IMAGE PROCESSING], we introduced the Kronecker array transform (KAT), a fast transform for imaging with separable arrays. Given a source distribution, the KAT produces the spectral matrix which would be measured by a separable sensor array. In Part II, we establish connections between the KAT, beamforming and 2-D convolutions, and show how these results can be used to accelerate classical and state of the art array imaging algorithms. We also propose using the KAT to accelerate general purpose regularized least-squares solvers. Using this approach, we avoid ill-conditioned deconvolution steps and obtain more accurate reconstructions than previously possible, while maintaining low computational costs. We also show how the KAT performs when imaging near-field source distributions, and illustrate the trade-off between accuracy and computational complexity. Finally, we show that separable designs can deliver accuracy competitive with multi-arm logarithmic spiral geometries, while having the computational advantages of the KAT.

MODELING THE UNVOICED COMPONENT IN THE CANONICAL REPRESENTATION OF SPEECH

The canonical representation of speech constitutes a perfect reconstruction (PR) analysis-synthesis system. Its parameters are the autoregressive (AR) model coefficients, the pitch period and the voiced and unvoiced components of the excitation represented as transform coefficients. Each set of parameters may be operated on independently. A time-frequency unvoiced excitation (TFUNEX) model is proposed that has high time resolution and selective frequency resolution. Improved time-frequency fit is obtained by using for antialiasing cancellation the clustering of pitch-synchronous transform tracks defined in the modulation transform domain. The TFUNEX model delivers high-quality speech while compressing the unvoiced excitation representation about 13 times over its raw transform coefficient representation for wideband speech.

Stochastic stability analysis for the constant-modulus algorithm

We derive an easy-to-compute approximate bound for the range of step-sizes for which the constant-modulus algorithm (CMA) will remain stable if initialized close to a minimum of the CM cost function. Our model highlights the influence, of the signal constellation used in the transmission system: for smaller variation in the modulus of the transmitted symbols, the algorithm will be more robust, and the steady-state misadjustment will be smaller. The theoretical results are validated through several simulations, for long and short filters and channels.