In recent years, WiFi-based device-free localization (DFL) has attracted attentions due to the rapid development of location-based applications. The performance data-driven DFL models highly relies on quality fingerprint. However, it is difficult obtain high-quality fingerprints in cluttered environments various uncertainties, such as environmental dynamics. To mitigate effects this article proposes a variance-constrained local–global modeling method enhance performance. be specific,...

In this brief, an optimal control scheme based on adaptive dynamic programming (ADP) is developed to solve infinite-horizon problems of continuous-time complex-valued nonlinear systems. A new performance index function established the basis state and control. Using system transformations, transformed into a real-valued one, which overcomes Cauchy-Riemann conditions effectively. With function, ADP method obtain law by using neural networks. compensation controller compensate approximation...

The classification of electrocardiograms (ECG) plays an important role in the clinical diagnosis heart disease. This paper proposes effective system development and implementation for ECG based on faster regions with a convolutional neural network (Faster R-CNN) algorithm. original one-dimensional signals contain preprocessed patient some recordings from MIT-BIH database this experiment. Each beat was transformed into two-dimensional image experimental training sets test sets. As result, we...

Vital signs, such as respiration rate (RR) and heart (HR), are essential for human health status assessment. The radar could detect RR HR in a noncontact manner by sensing the repetitive chest wall movement caused cardiopulmonary activity, which is attractive due to more comfortable experience better privacy protection. However, displacement heartbeat much smaller than that respiration, weak component may be easily overwhelmed harmonics, noise, clutter, making it difficult achieve accurate...

Human activity recognition (HAR) is a key technology in the field of human–computer interaction. Unlike systems using sensors or special devices, WiFi channel state information (CSI)-based HAR are noncontact and low cost, but they limited by high computational complexity poor cross-domain generalization performance. In order to address above problems, reconstructed CSI tensor deep learning based lightweight system (Wisor-DL) proposed, which firstly reconstructs signals with sparse signal...

This paper is concerned with the estimation problem for discrete-time stochastic linear systems multiple packet dropouts. Based on a recently developed model multiple-packet dropouts, original system transferred to parameter by augmentation of state and measurement. The optimal full-order filter form employing received outputs at current last time instants investigated. solution given in terms Riccati difference equation governed arrival rate. reduced standard Kalman when there are no...

Energy-based multisource localization is an important research problem in wireless sensor networks (WSNs). Existing algorithms for this problem, such as multiresolution (MR) search and exhaustive methods, are of either high computational complexity or low estimation accuracy. In paper, efficient expectation-maximization (EM) algorithm maximum-likelihood (ML) presented energy-based WSNs using acoustic sensors. The basic idea the to decompose each sensor's energy measurement, which a...

Gas utilization ratio (GUR) is an important indicator used to measure the operating status and energy consumption of blast furnaces (BFs). In this paper, we present a soft-sensor approach, i.e., novel online sequential extreme learning machine (OS-ELM) named DU-OS-ELM, establish data-driven model for GUR prediction. firstly, old collected data are discarded gradually newly acquired given more attention through dynamic forgetting factor (DFF), depending on estimation errors enhance tracking...

Source localization based on time-difference-of-arrival (TDOA) measurements from spatially separated sensors is an important problem in sensor networks. In this paper, we study the optimal geometries of a team networked for TDOA-based problem, taking into account priori uncertainty source location. Two types TDOA pairing methods, namely, centralized and decentralized , are considered. Analytic solutions to ideal case derived both static movable cases. case, geometry design investigated under...

In this paper, an intelligent data-driven optimization scheme is proposed for finding the proper burden surface distribution, which exerts large influences on keeping blast furnace running smoothly in energy-efficient state. scheme, production indicators prediction models are first developed using a kernel extreme learning machine algorithm. To heel, decision presented as multiobjective problem time and solved by modified two-stage strategy to generate initial setting values of surface....

Ubiquitous WiFi signals not only provide fundamental communications for a large number of Internet Things devices, but also enable to estimate target's location in contactless manner. However, most the existing device-free localization (DFL) methods utilize time dynamics received signals, leading inaccurate DFL cluttered indoor environments. Because different layouts environments and deployments devices cause mathematical distributions data collected from In this article, multiple kernel...

Recent advances in WiFi-based device-free localization (DFL) mainly focus on stationary scenarios and ignore the environmental dynamics, hindering large-scale implementation of DFL technique. In order to enhance performance nonstationary environments, this article, a novel multidomain collaborative extreme learning machine (MC-ELM)-based framework is proposed. Specifically, whole environment first divided into several subdomains depending distributions collected data using clustering...

Clinical notes contain contextualized information beyond structured data related to patients' past and current health status.

Applications for wireless sensor networks may be decomposed into the deployment of tasks on different nodes in network. Task allocation algorithms assign these to specific network execution. Given resource-constrained and distributed nature (WSNs), existing static (offline) task scheduling not practical. Therefore there is a need an adaptive scheme that accounts characteristics WSN environment such as unexpected communication delay node failure. In this paper, we focus WSNs which performed...

Source localization is an important application of wireless sensor networks (WSNs). Many types sensors can be used for source localization, e.g., range sensors, bearing and time-difference-of-arrival (TDOA) based etc. It well known that relative sensor-source geometry significantly affect the performance any particular algorithm. Existing works in literature mainly deal with analysis homogeneous sensors. However, real applications, different may utilized localization. Hence, this paper, we...

Indoor positioning has emerged as a widely used application of Wi-Fi wireless networks. A region-based fingerprinting approach is presented for indoor in This proposed method compares the fingerprint tag with that group reference points, instead an individual point. With position estimate obtained, and inertial measurement unit integrated tag, stochastic system model adopted to track target's when it piecewise constant velocity motion The utilizes estimates measurements sensing data control...

The TDOA-based source localization problem in sensor networks is considered with node location uncertainty. A total least squares (TLSs) algorithm developed by a linear closed-form solution for this problem, and the uncertainty of formulated as perturbation. sensitivity TLS also analyzed. Simulation results show its improved performance against classic approaches.

Indoor positioning has emerged as a widely used application of Wi-Fi wireless networks. Fingerprinting techniques can provide low-cost and high-accuracy localization solution by utilizing in-building communication infrastructures. However, existing fingerprinting algorithms are not resistant to outliers, for example, the accidental environment changes, access point (AP) attacks. Another drawback is that traditional K nearest neighbor (KNN) algorithm in literature may select candidate...

Device-free localization (DFL) is becoming one of the new technologies in wireless field, due to its advantage that target be localized does not need attached any electronic device. In radio-frequency (RF) DFL system, radio transmitters (RTs) and receivers (RXs) are used sense collaboratively, location can estimated by fusing changes received signal strength (RSS) measurements associated with links. this paper, we will propose an extreme learning machine (ELM) approach for DFL, improve...