Search

Seeds age during storage, resulting in a decline in germination and seedling quality. Seed quality tests are important to monitor this decline. However, such tests are usually destructive and require large seed numbers and long time. For coffee seeds the standard germination test and assessment of seedling quality takes 30 days. Biospeckle has been used previously as a non-destructive optical tool to monitor biological activity in a range of tissues. Biospeckle was applied 3–6 days after imbibition (DAI) to investigate an association with coffee seedling quality after 30 days. Two distinct areas of biospeckle activity were demonstrated, concurring with the locations of the embryonic axis and the cotyledons in the apical and central seed parts, respectively. Moisture content analysis revealed that embryos of imbibed seeds contained more water than endosperm. Different areas within the endosperm did not differ in moisture content, while the moisture content of the axis was higher than that of the cotyledons, and this did not change from 4 DAI. Therefore, it was concluded that high biospeckle activity was not the result of increased water content in any seed part, but more likely of growth and metabolism in the axis and cotyledons, which had been described previously. A threshold biospeckle ratio apical : central of 1.02 after 6 days distinguished between seeds that produced dead and viable seedlings after 30 days and provided similar results as a tetrazolium test, a widely acknowledged but destructive test for seed quality. Thus, biospeckle data provided a non-destructive early parameter for seedling quality, based on embryo growth during germination.

This work presents a statistical analysis of a jointly optimized beamformer-assisted acoustic echo canceler (AEC). It is shown that the constrained joint optimization problem can be formulated so that it becomes equivalent to the linearly-constrained minimum variance problem. The new formulation leads to analytical models that can be used to predict the transient performance of adaptive wideband beamformers. A stochastic model is derived for the transient and steady-state behaviors of the residual echo power. A convergence analysis provides a stability bound for the adaptation step-size. Monte Carlo simulations illustrate the accuracy of the model, which is then used to provide design guidelines. Application of the new model confirms previous experimental findings that the same cancellation performance of a single-microphone AEC can be achieved with a shorter AEC when the possibility of spatial filtering is available.

The traditional concept that effector T helper (Th) responses are mediated by Th1/Th2 cell subtypes has been broadened by the recent demonstration of two new effector T helper cells, the IL-17 producing cells (Th17) and the follicular helper T cells (Tfh). These new subsets have many features in common, such as the ability to produce IL-21 and to express the IL-23 receptor (IL23R), the inducible co-stimulatory molecule ICOS, and the transcription factor c-Maf, all of them essential for expansion and establishment of the final pool of both subsets. Tfh cells differ from Th17 by their ability to home to B cell areas in secondary lymphoid tissue through interactions mediated by the chemokine receptor CXCR5 and its ligand CXCL13. These CXCR5+ CD4+ T cells are considered an effector T cell type specialized in B cell help, with a transcriptional profile distinct from Th1 and Th2 cells. The role of Tfh cells and its primary product, IL-21, on B-cell activation and differentiation is essential for humoral immunity against infectious agents. However, when deregulated, Tfh cells could represent an important mechanism contributing to exacerbated humoral response and autoantibody production in autoimmune diseases. This review highlights the importance of Tfh cells by focusing on their biology and differentiation processes in the context of normal immune response to infectious microorganisms and their role in the pathogenesis of autoimmune diseases.

In this paper, we employ the widely linear adaptive processing technique in digital communication channel equalization. We present two new techniques for supervised and unsupervised equalization. In the supervised technique the multi-split transform is aggregated to the widely linear processing, using a power normalized and time-varying step-size LMS algorithm. The unsupervised technique consists of a widely linear adaptive prediction-error filter using the time-varying step-size LMS algorithm proposed by Kwong and Johnston. We show that this technique can invert non-minimum phase channels. The main advantages of the proposed equalizers are the low computational complexity and better performance in terms of convergence rate and accuracy, when compared to the conventional equalization techniques. Simulation results show that the widely linear equalizers have a good performance.

In this paper the effect of channel estimation errors in single carrier systems using frequency domain widely linear iterative equalization is investigated. It was found out that when compared to their strictly linear versions their error performance is more robust with respect to these errors. They do not have the high error floor present in the error performance of strictly linear systems that do not take into account the channel estimation error into account; even when this error is considered their performance is slightly better.

This paper proposes a new structure for split transversal filtering and introduces the optimum split Wiener filter. The approach consists of combining the idea of split filtering with a linearly constrained optimization scheme. Furthermore, a continued split procedure, which leads to a multisplit filter structure, is considered. It is shown that the multisplit transform is not an input whitening transformation. Instead, it increases the diagonalization factor of the input signal correlation matrix without affecting its eigenvalue spread. A power normalized, time-varying step-size least mean square (LMS) algorithm, which exploits the nature of the transformed input correlation matrix, is proposed for updating the adaptive filter coefficients. The multisplit approach is extended to linear-phase adaptive filtering and linear prediction. The optimum symmetric and antisymmetric linear-phase Wiener filters are presented. Simulation results enable us to evaluate the performance of the multisplit LMS algorithm.

Beamformer-assisted acoustic echo cancelers have raised a lot of interest lately. The same performance can be obtained with a reduced length acoustic echo canceler (AEC) as the beamformer (BF) performs spatial cancellation. Structures that jointly optimize the BF and the AEC coefficients are preferred in order to exploit synergies. Analytical models have been already derived for the behavior of the direct form implementation of such systems adapted using the constrained least-mean square (CLMS) algorithm. This work extends the analysis to the popular generalized sidelobe canceler (GSC) structure, while allowing for a positive definite step-size matrix. Analytical models are derived for the mean and mean-square behaviors of the adaptive coefficients. Simulation results are shown to be in excellent agreement with the performance predicted by the theory.

This work presents a statistical analysis of a beamformer-assisted acoustic echo canceler (AEC). A new formulation leads to analytical models that can also be used to predict the transient performance of adaptive wideband beamformers. Monte Carlo simulations illustrate the accuracy of the model, which is then used to provide design guidelines. Application of the new model confirms previous experimental findings that the same cancellation performance of a single-microphone AEC can be achieved with a shorter AEC when the possibility of spatial filtering is available.

The project of wireless communication systems with the purpose to minimize the bit error rate is a current problem and it is motivated increasingly by the growing demand for higher data rates. In this sense, this work proposes a frequency, time and space diversity technique, which applies a space-time code with block repetitions such that space-frequency diversity is obtained, combined with the time spreading of OFDM symbol through Hadamard transform. Simulations showed that performance gain was achieved in high Doppler frequency scenarios followed by improved results at degraded frequency selective fading channels modeled by Rayleigh distributions.

Acoustic echo cancellation constitutes a major challenge for full-duplex communication and human-machine speech interaction. Beamforming is a well-known technique for suppression of local interferers, including acoustic echoes. Those techniques can be combined to jointly achieve better echo cancellation at an additional computational cost. Experimental results available in the literature show significant increase in echo cancellation performance when assisted by a beamformer. Different implementation schemes have been proposed. Performance comparisons of these solutions have been mostly experimental, which limits the generalization of the results. This work compares the optimal solutions provided by the original cascaded BF-AEC structure and by the alternative scheme that jointly optimizes the beamformer and the acoustic echo canceler coefficients.

This paper presents a GSC-type structure for the FIR-IFIR hybrid echo canceller and the optimum filters are defined. The measure of echo cancellation performance is presented, which is a function of the input signal correlation, of the sparseness degree and of the interpolator parameters. Furthermore, the LMS algorithm for updating the filter coefficients in adaptive systems is also developed. Simulation results illustrate the effectiveness of the new approach to this FIR-IFIR hybrid filtering problem for both white and colored input noise.

This paper proposes a new blind equalization scheme based on widely linear (WL) prediction. It permits to compensate non-minimum phase channels with or without spectral nulls, since the received signal can be interpreted as a convolution of a real-valued data sequence and a complex baseband channel. Such a transmission model applies, for instance, to the ASK, OQAM and binary MSK-type modulations. The WL prediction technique uses a linear combination of the complex delayed samples of the received signal and its complex conjugate to predict the current sample. The proposed WL blind equalizer presents a low computational complexity and a higher convergence rate as compared to others blind equalization techniques.

Multiuser processing, using an antenna array, has emerged as a suitable solution for capacity increase in wireless systems. The use of an antenna array reduces the multiuser interference, allowing two or more users to share systems resources in an efficient way. The use of a Linearly Constrained Minimum Variance (LCMV) criterion to optimize the antenna array weights has been proved to be a good solution for multiuser processing. This work presents an unified view of LCMV beamforming, including a solution that avoids direction of arrival (DOA) estimation and is able to cope with angular spread. An adaptive versions of the resulting technique is also presented. Moreover, we evaluate the performance of the proposed techniques in non-zero angular spread and non-stationary environments. The results provide an overview of the potential of LCMV techniques in multiuser wireless communication systems.

This paper presents a statistical analysis of the filtered-x LMS algorithm about the steady-state solution. Analytical models are derived for the mean weight-error vector and the mean square error behaviors which are simpler than existing models. The simpler models allow the determination of new convergence and steady-state results that should prove useful for design purposes. Simulation results display excellent agreement between theoretical predictions and Monte Carlo simulation results. Examples show that the new theory can be used to predict both transient and steady-state behaviors of the FXLMS algorithm in active control of sound and vibration.

A new space diversity scheme for multipath channels is proposed. Split-ST-OFDM makes use of split-processing to improve the performance of regular ST-OFDM. The novel approach is shown to be more general than the case where the Hadamard transform is used to explore the frequency diversity inherent to the multipath channel. Computer simulations show large gains of the proposed scheme over regular ST-OFDM for the case of terrestrial digital TV channels, at the expense of a very low additional computational complexity.

In this paper, we investigate the use of some classical techniques for accelerating the convergence of the LMS algorithm in widely linear (WL) adaptive processing. The application of channel equalizing is considered. Simulation results permit to verify that the normalized LMS strategy presents the best performance as far as a reduction of the trade-off between the convergence rate and steady-state error is concerned.

Cascaded integrator comb (CIC) filters are used to realize computationally efficient decimation, interpolation or sample rate conversion. However, since CIC filters have a limited number of tuning parameters and exhibit a passband droop, their use in Software Defined Radio (SDR) systems may be limited. In this paper, we propose an alternative structure to CIC filters that, at the expenses of a higher computational effort, is suitable for SDR systems.

This paper presents a simple and efficient analytical model for the convergence behavior of the filtered-x LMS (FXLMS) algorithm with Gaussian input data. Deterministic recursions are obtained for the mean weight vector and the mean square error. The new model predicts the algorithm behavior for a wide range of practical applications. This model can be employed either when the adaptive filter lies after the secondary path filter or when their order is reversed in the cascade sequence. Simulation results display excellent agreement with the behavior predicted by the theoretical model for transient and steady-state phases of adaptation. The new simple model should be instrumental in designs systems for active control of sound and vibration

A simple and efficient implementation of multi-split adaptive filtering with complex parameters is introduced. The proposed scheme shares the same butterfly structure as for the case of real-valued data. This approach guarantees a simple and low-cost implementation in VLSI, FPGA or DSP. Simulation results show the performance of the multi-split LMS algorithm in the case of adaptive equalization of a 4-QAM communication system.

The paper presents a statistical analysis of the multi-split LMS algorithm. Deterministic recursions are obtained for the mean weight vector and the mean square error. Simulation results display excellent agreement with the theoretical predictions, and enable us to validate the proposed models for both transient and steady-state behaviors.

This paper presents the multisplit LMS adaptive GSC for narrowband beamforming. We start from the classical GSC structure and then embed the multisplit preprocessing into the GSC signal blocking matrix. This operation leaves the multisplit LMS adaptive GSC with the same computational complexity as the classical LMS adaptive GSC. Interference cancellation simulations show that the adaptation of the GSC structure with the proposed multisplit scheme can be much faster when compared with the classical LMS algorithm.

This paper presents an analysis that justifies the improved performance of the multi-split LMS algorithm. It is shown that instead of reducing the eigenvalue ratio, the multi-split operation increases the diagonalization factor of the transformed input signal autocorrelation matrix, which assists the power normalized and time-varying step-size LMS algorithm used for updating the single parameters independently. Case studies and simulation results enable us to evaluate the improved performance of the multi-split LMS algorithm.

A robust approach to implement the FLS algorithm for linearly constrained adaptive filtering is derived in this work. The robustness is provided by means of an additional correcting term which is also updated by a LS procedure. In fact, the novel algorithm works as the LS version of the classical LMS-based Frost algorithm. Simulation results with a long data input sequence show the performance of the proposed technique. >

A novel transversal split filter configuration is proposed and the split optimum Wiener filter is introduced, as well as the symmetric and antisymmetric linear phase Wiener filter. The approach consists of combining the idea of split filtering with a linearly constrained optimization scheme. Then, the continuously split procedure is introduced and the multi-split adaptive filter is derived. It is also shown that such a structure can be viewed as a Hadamard-domain adaptive filter when the number of coefficients is set to a power of two. Simulation results obtained with the normalized LMS algorithm are presented and compared with DCT-domain adaptive filter.

A new structure for adaptive interpolated finite impulse response (AFIR) filtering is presented, in which the RLS algorithm can be directly applied for updating only the nonzero coefficients of the sparse filter. The approach is based on the linearly-constrained filter called the generalized sidelobe canceller. The performance of the RLS algorithm applied to the AIFIR filtering is illustrated by simulations and compared with that of the LMS algorithm.

An extension of the field of split processing technique is presented. A new structure for the split transversal filter is proposed and the split optimum Wiener filter is introduced, as well as its symmetric and antisymmetric versions of linear phase. The approach is based on the linearly-constrained filter called generalized sidelobe canceller. The performances of both LMS and RLS algorithms applied to the proposed split structure are illustrated by simulations and compared with those of the conventional LMS and RLS adaptive systems.

We introduce the optimum interpolated Wiener filter, which resulted from an original and elegant linearly-constrained approach to the interpolated transversal filtering problem. An accurate analytical model for the mean coefficient behavior of LMS-AIFIR filters is also presented. Simulation results illustrate the effectiveness of the proposed model.

A fast least squares algorithm is proposed for adaptive filtering with linear constraints. The algorithm is exact, with a computational complexity proportional to NK+K/sup 2/+N+K where N is the number of the filter coefficients and K is the number of constraints. The approach consists of obtaining the adaptation gain by means of a fast least squares (FLS) algorithm and using this gain in the recursive calculations of the parameters related to the constraints. The recursive procedures are carried out by using the matrix inversion lemma. The good performance of the proposed method is illustrated by some simulation results. The algorithm can be used in several applications such as array processing, adaptive beamforming, spectral analysis and telecommunications. >

This paper presents the implementation of blind equalizers with a new filtering structure, the split transversal filter. The aim is to improve the robustness of known blind algorithms. Comparisons between the new scheme and the traditional structure for three of the Bussgang techniques are presented. While the traditional equalizers are attracted by a local minimum, the split equalizer can avoid them and reach the global solution.