# IEEE Transactions on Cybernetics

## Issue 3 • March 2019

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## Filter Results

Displaying Results 1 - 25 of 37

Publication Year: 2019, Page(s):C1 - 733
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• ### IEEE Transactions on Cybernetics

Publication Year: 2019, Page(s): C2
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• ### Remote Nonlinear State Estimation With Stochastic Event-Triggered Sensor Schedule

Publication Year: 2019, Page(s):734 - 745
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This paper concentrates on the remote state estimation problem for nonlinear systems over a communication-limited wireless sensor network. Because of the non-Gaussian property caused by nonlinear transformation, the unscented transformation technique is exploited to obtain approximate Gaussian probability distributions of state and measurement. To reduce excessive data transmission, uncontrollable... View full abstract»

• ### Multiplicative Update Methods for Incremental Quantile Estimation

Publication Year: 2019, Page(s):746 - 756
Cited by:  Papers (1)
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We present a novel lightweight incremental quantile estimator which possesses far less complexity than the Tierney’s estimator and its extensions. Notably, our algorithm relies only on tuning one single parameter which is a plausible property which we could only find in the discretized quantile estimator Frugal. This makes our algorithm easy to tune for better performance. Furthermore, our algorit... View full abstract»

• ### Distributed Adaptive Event-Triggered Fault-Tolerant Consensus of Multiagent Systems With General Linear Dynamics

Publication Year: 2019, Page(s):757 - 767
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In this paper, the distributed adaptive event-triggered fault-tolerant consensus of general linear multiagent systems (MASs) is considered. First, in order to deal with multiplicative fault, a distributed event-triggered consensus protocol is designed. Using distributed adaptive online updating strategies, the computation of the minimum eigenvalue of Laplacian matrix is avoided. Second, some adapt... View full abstract»

• ### Effects of Target Signal Shape and System Dynamics on Feedforward in Manual Control

Publication Year: 2019, Page(s):768 - 780
Cited by:  Papers (1)
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The human controller (HC) in manual control of a dynamical system often follows a visible and predictable reference path (target). The HC can adopt a control strategy combining closed-loop feedback and an open-loop feedforward response. The effects of the target signal waveform shape and the system dynamics on the human feedforward dynamics are still largely unknown, even for common, stable, vehic... View full abstract»

• ### Error Correcting Input and Output Hashing

Publication Year: 2019, Page(s):781 - 791
Cited by:  Papers (1)
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Most learning-based hashing algorithms leverage sample-to-sample similarities, such as neighborhood structure, to generate binary codes, which achieve promising results for image retrieval. This type of methods are referred to as instance-level encoding. However, it is nontrivial to define a scalar to represent sample-to-sample similarity encoding... View full abstract»

• ### Consensus of Leader-Following Multiagent Systems: A Distributed Event-Triggered Impulsive Control Strategy

Publication Year: 2019, Page(s):792 - 801
Cited by:  Papers (1)
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This paper investigates the leader-following consensus problem of multiagent systems using a distributed event-triggered impulsive control method. For each agent, the controller is updated only when some state-dependent errors exceed a tolerable bound. The control inputs will be carried out by actor only at event triggering impulsive instants. According to the Lyapunov stability theory and impulsi... View full abstract»

• ### Multiscale Amplitude Feature and Significance of Enhanced Vocal Tract Information for Emotion Classification

Publication Year: 2019, Page(s):802 - 815
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In this paper, a novel multiscale amplitude feature is proposed using multiresolution analysis (MRA) and the significance of the vocal tract is investigated for emotion classification from the speech signal. MRA decomposes the speech signal into number of sub-band signals. The proposed feature is computed by using sinusoidal model on each sub-band signal. Different emotions have different impacts ... View full abstract»

• ### Improved Space Forest: A Meta Ensemble Method

Publication Year: 2019, Page(s):816 - 826
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The performance of the ensemble algorithms is related with the individual accuracy of the base learners and their results diversity. Individual accuracy of a base learner is directly related to the similarity between the original training set and the base learner’s training set. When a modified training set by randomly selecting features/classes/samples is given to the base learners, the diversity... View full abstract»

• ### Decentralized Adaptive Fuzzy Secure Control for Nonlinear Uncertain Interconnected Systems Against Intermittent DoS Attacks

Publication Year: 2019, Page(s):827 - 838
Cited by:  Papers (1)
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Cyber-physical systems (CPSs) are naturally highly interconnected and complexly nonlinear. This paper investigates the problem of decentralized adaptive output feedback control for CPSs subject to intermittent denial-of-service (DoS) attacks. The considered CPSs are modeled as a class of nonlinear uncertain strict-feedback interconnected systems. When a DoS attack is active, all the state variable... View full abstract»

• ### Spatial–Temporal Recurrent Neural Network for Emotion Recognition

Publication Year: 2019, Page(s):839 - 847
Cited by:  Papers (3)
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In this paper, we propose a novel deep learning framework, called spatial–temporal recurrent neural network (STRNN), to integrate the feature learning from both spatial and temporal information of signal sources into a unified spatial–temporal dependency model. In STRNN, to capture those spatially co-occurrent variations of human emotions, a multidirectional recurrent neural network (RNN) layer is... View full abstract»

• ### Data-Driven Distributed Output Consensus Control for Partially Observable Multiagent Systems

Publication Year: 2019, Page(s):848 - 858
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This paper is concerned with a class of optimal output consensus control problems for discrete linear multiagent systems with the partially observable system state. Since the optimal control policy depends on the full system state which is not accessible for a partially observable system, traditionally, distributed observers are employed to recover the system state. However, in many situations, th... View full abstract»

• ### An Efficient Nondominated Sorting Algorithm for Large Number of Fronts

Publication Year: 2019, Page(s):859 - 869
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Nondominated sorting is a key operation used in multiobjective evolutionary algorithms (MOEA). Worst case time complexity of this algorithm is ${O(MN^{2})}$ , where ${N}$ is the number of solutions and ${M}$ View full abstract»

• ### Distributed $H_\infty$ State Estimation Over a Filtering Network With Time-Varying and Switching Topology and Partial Information Exchange

Publication Year: 2019, Page(s):870 - 882
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This paper is concerned with the distributed ${H_\infty }$ state estimation for a discrete-time target linear system over a filtering network with time-varying and switching topology and partial information exchange. Both filtering network topology switching and partial information exchange between filters are simultaneously ... View full abstract»

• ### Bifurcation and Oscillatory Dynamics of Delayed Cyclic Gene Networks Including Small RNAs

Publication Year: 2019, Page(s):883 - 896
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It has been demonstrated in a large number of experimental results that small RNAs (sRNAs) play a vital role in gene regulation processes. Thus, the gene regulation process is dominated by sRNAs in addition to messenger RNAs and proteins. However, the regulation mechanism of sRNAs is not well understood and there are few models considering the effect of sRNAs. So it is of realistic biological back... View full abstract»

• ### Small Fault Detection for a Class of Closed-Loop Systems via Deterministic Learning

Publication Year: 2019, Page(s):897 - 906
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In this paper, based on the deterministic learning (DL) theory, an approach for detection for small faults in a class of nonlinear closed-loop systems is proposed. First, the DL-based neural control approach and identification approach are employed to extract the knowledge of the control effort that compensates the fault dynamics (change of the control effort) and the fault dynamics (the change of... View full abstract»

• ### Large-Scale Robust Semisupervised Classification

Publication Year: 2019, Page(s):907 - 917
Cited by:  Papers (2)
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Semisupervised learning aims to leverage both labeled and unlabeled data to improve performance, where most of them are graph-based methods. However, the graph-based semisupervised methods are not capable for large-scale data since the computational consumption on the construction of graph Laplacian matrix is huge. On the other hand, the substantial unlabeled data in training stage of semisupervis... View full abstract»

• ### Multiobjective Learning in the Model Space for Time Series Classification

Publication Year: 2019, Page(s):918 - 932
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A well-defined distance is critical for the performance of time series classification. Existing distance measurements can be categorized into two branches. One is to utilize handmade features for calculating distance, e.g., dynamic time warping, which is limited to exploiting the dynamic information of time series. The other methods make use of the dynamic information by approximating the time ser... View full abstract»

• ### Dimension Reduction for Non-Gaussian Data by Adaptive Discriminative Analysis

Publication Year: 2019, Page(s):933 - 946
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High-dimensional non-Gaussian data are ubiquitous in many real applications. Face recognition is a typical example of such scenarios. The sampled face images of each person in the original data space are more closely located to each other than to those of the same individuals due to the changes of various conditions like illumination, pose variation, and facial expression. They are often non-Gauss... View full abstract»

• ### Taste Recognition in E-Tongue Using Local Discriminant Preservation Projection

Publication Year: 2019, Page(s):947 - 960
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Electronic tongue (E-Tongue), as a novel taste analysis tool, shows a promising perspective for taste recognition. In this paper, we constructed a voltammetric E-Tongue system and measured 13 different kinds of liquid samples, such as tea, wine, beverage, functional materials, etc. Owing to the noise of system and a variety of environmental conditions, the acquired E-Tongue data shows inseparable ... View full abstract»

• ### Adaptive Fuzzy Containment Control of Nonlinear Systems With Unmeasurable States

Publication Year: 2019, Page(s):961 - 973
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The adaptive fuzzy containment control problem is discussed for high-order systems with unknown nonlinear dynamics and unmeasurable states guided by multiple dynamic leaders. A high gain observer is introduced to reconstruct the system states. Then, utilizing fuzzy logic systems to model followers’ dynamics, an observer-based adaptive fuzzy containment control approach is presented using only the ... View full abstract»

• ### Game-Based Memetic Algorithm to the Vertex Cover of Networks

Publication Year: 2019, Page(s):974 - 988
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The minimum vertex cover (MVC) is a well-known combinatorial optimization problem. A game-based memetic algorithm (GMA-MVC) is provided, in which the local search is an asynchronous updating snowdrift game and the global search is an evolutionary algorithm (EA). The game-based local search can implement (k,l)-exchanges for various numbers of View full abstract»

• ### An Interclass Margin Maximization Learning Algorithm for Evolving Spiking Neural Network

Publication Year: 2019, Page(s):989 - 999
Cited by:  Papers (1)
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This paper presents a new learning algorithm developed for a three layered spiking neural network for pattern classification problems. The learning algorithm maximizes the interclass margin and is referred to as the two stage margin maximization spiking neural network (TMM-SNN). In the structure learning stage, the learning algorithm completely evolves the hidden layer neurons in the first epoch. ... View full abstract»

• ### Event-Triggered Coordination for Formation Tracking Control in Constrained Space With Limited Communication

Publication Year: 2019, Page(s):1000 - 1011
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In this paper, the formation tracking control is studied for a multiagent system (MAS) with communication limitations. The objective is to control a group of agents to track a desired trajectory while maintaining a given formation in nonomniscient constrained space. The role switching triggered by the detection of unexpected spatial constraints facilitates efficiency of event-triggered control in ... View full abstract»

## Aims & Scope

The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Prof. Jun Wang
Dept. of Computer Science
City University of Hong Kong
Kowloon Tong, Kowloon, Hong Kong
Tel: +852 34429701
Email: jwang.cs@cityu.edu.hk