Phosphorus (P) is the second most important nutrient after nitrogen (N) and can greatly diminish plant productivity if P supply not adequate. Plants respond to soil availability by adjusting root biomass maintain uptake due use. In spite of our vast knowledge on effects growth, how functionally model enhanced allocation in low environments fully explored. We develop a dynamic based principle optimal carbon (C) investigate growth functional response contrasting levels availability. By...

This paper presents a novel rotation-invariant image retrieval scheme based on transformation of the texture information via steerable pyramid. First, we fit distribution subband coefficients using joint alpha-stable sub-Gaussian model to capture their non-Gaussian behavior. Then, apply normalization process in order Gaussianize coefficients. As result, feature extraction step consists estimating covariances between normalized pyramid The similarity two distinct images is measured by...

This paper introduces a novel framework for compressive sensing of biomedical ultrasonic signals based on modelling data with stable distributions. We propose an approach to ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> norm minimisation that employs the iteratively reweighted least squares (IRLS) algorithm but in which parameter p is judiciously chosen by relating it characteristic exponent underlying alpha-stable distributed data....

This paper proposes a novel localization technique based on multivariate Gaussian modeling of the signal strength measurements collected from several access points (APs) at different locations. It considers discretized grid-like form environment and computes signature each cell grid. At run time system compares unknown position with using Kullback-Leibler Divergence estimation (KLD) between their corresponding probability densities. The evaluates performance proposed it other statistical...

Traditional bearing estimation techniques perform Nyquist-rate sampling of the received sensor array signals and as a result they require high storage transmission bandwidth resources. Compressed sensing (CS) theory provides new paradigm for simultaneously compressing signal using small subset random incoherent projection coefficients, enabling potentially significant reduction in computation costs. In this paper, we develop Bayesian CS (BCS) approach estimating target bearings based on...

Traditional compressive sensing (CS) primarily assumes light-tailed models for the underlying signal and/or noise statistics.Nevertheless, this assumption is not met in case of highly impulsive environments, where non-Gaussian infinitevariance processes arise components.This drives traditional sparse reconstruction methods to failure, since they are incapable suppressing effects heavy-tailed sampling noise.The family symmetric alphastable (SαS) distributions, as a powerful tool modeling...

This paper introduces a new technique for reconstruction of biomedical ultrasound images from simulated compressive measurements, based on modeling data with stable distributions. The proposed algorithm exploits two types prior information: one hand, our approach is the observation that RF echoes are best characterized statistically by alpha-stable On other through knowledge acquisition process, support in Fourier domain can be easily inferred. Together, these facts form basis an ℓ <sub...

Due to the importance of lower bounding distances and attractiveness symbolic representations, family aggregate approximations (SAX) has been used extensively for encoding time series data. However, typical SAX-based methods rely on two restrictive assumptions; Gaussian distribution equiprobable symbols. This paper proposes novel data-driven distinguished by their discretization steps. The first representation, oriented general data compaction indexing scenarios, is based combination kernel...

Active range imaging (RI) systems utilize actively controlled light sources emitting laser pulses that are subsequently recorded by an system and used for depth profile estimation. Classical RI limited their need a large number of frames required to obtain high resolution information. In this work, we propose approach motivated the recently proposed compressed sensing framework dramatically reduce necessary frames. Compressed gated employs random gating mechanism along with state-of-the-art...

Network traffic load in an IEEE802.11 infrastructure arises from the superposition of accessed by wireless clients associated with access points (APs). An accurate characterization these data can be beneficial modelling network and addressing a variety problems including coverage planning, resource reservation monitoring for anomaly detection. This study focuses on statistical analysis measured campus-wide at each AP.

This paper addresses the construction of a novel efficient rotation-invariant texture retrieval method that is based on alignment in angle signatures obtained via steerable sub-Gaussian model. In our proposed scheme, we first construct multivariate model, where fractional lower-order moments given image are associated with those its rotated versions. The feature extraction step consists estimating so-called covariations between orientation subbands corresponding pyramid at same or adjacent...

In this paper, the principles of compressive sensing are exploited for joint reconstruction an ensemble biomedical ultrasound RF echoes, using a highly reduced set random measurements. Temporal correlations between distinct echoes taken into account during reconstruction, which results in reduction required number measurements, while also increasing quality. The efficiency recent state-of-the-art methods is evaluated on real data, to highlight importance accounting temporal reconstruction....

This paper introduces and evaluates the Gesture-Keeper, a robust hand-gesture recognition system based on wearable inertial measurements unit (IMU). The identification of time windows where gestures occur, without relying an explicit user action or special gesture marker, is very challenging task. To address this problem, GestureKeeper identifies start by exploiting underlying dynamics associated series using recurrence quantification analysis (RQA). RQA powerful method for nonlinear...

A novel context enhancement technique is presented to automatically combine images of the same scene captured at different times or seasons. unique characteristic algorithm its ability extract and maintain meaningful information in enhanced image while recovering surrounding by fusing background image. The input are first decomposed into multiresolution representations using Dual-Tree Complex Wavelet Transform (DT-CWT) with subband coefficients modelled as Cauchy random variables. Then,...

Abstract In this paper we propose an enhancement of recurrence quantification analysis (RQA) performance in extracting the underlying non-linear dynamics market index returns, under assumption data corrupted by additive white Gaussian noise. More specifically, first show that statistical distribution wavelet decompositions distinct returns is best fitted using members alpha-stable distributions family. Then, efficient maximum a posteriori (MAP) estimator applied on pairs coefficients at...

A novel statistical scheme is presented for the classification of shallow water acoustic signals according to environmental parameters medium through which they have propagated. An efficient way classify these important inverse procedures in underwater acoustics aiming at recovery geoacoustic an oceanic environment, using measurements field due source. issue this procedure determination “observable” signal (feature extraction), characterizes connection with recoverable parameters. The...

The ease of image storage and transmission in modern applications would be unfeasible without compression, which converts high-resolution images into a relatively small set significant transform coefficients. Due to the specific content many real-world they are highly sparse an appropriate orthonormal basis. inherent property compressed sensing (CS) theory working simultaneously as compression protocol, using subset random incoherent projection coefficients, enables potentially reduction...

Contemporary water distribution networks exploit information communication technologies (ICT) to monitor and control the behavior of network assets. Limited capability typically battery powered low-resourced devices, such as smart meters/sensors, have been used transfer from data centers for further analysis. Many companies deploy devices aiming last beyond 10-year mark. This prohibits use high-sample rate sensing therefore limiting knowledge we can obtain this data. However, reduction...

This paper is concerned with the use of reassigned wavelet transform for mode identification in shallow water acoustic propagation. Mode important inverse procedures underwater acoustics. An efficient way to recognize modal structure field when a single hydrophone available refer time frequency analysis recorded signal using transform. However, standard some cases may result an obscure representation dispersion curves. Thus, process proposed which brings improvements signal. achieved by...

Range Imaging (RI) has sparked an enthusiastic interest recently due to the numerous applications that can benefit from presence 3D data. One of most successful techniques for RI employs Time-of-Flight (ToF) cameras which emit and subsequently record laser pulses in order estimate distance between camera object. A limitation this class is requirement a large number frames have be captured generate high resolution depth maps. In work, we propose novel approach ToF based utilizes proposed...