# IEEE Transactions on Cybernetics

Includes the top 50 most frequently accessed documents for this publication according to the usage statistics for the month of

• ### Enhanced Computer Vision With Microsoft Kinect Sensor: A Review

Publication Year: 2013, Page(s):1318 - 1334
Cited by:  Papers (451)  |  Patents (25)
| | PDF (6865 KB) | HTML

With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the depth and visual information provided by the Kinect sensor opens up new opportunities to solve fundamental problems in computer vision. This paper presents a comprehensive review of recent Kinect-based computer vision al... View full abstract»

• ### A Generic Deep-Learning-Based Approach for Automated Surface Inspection

Publication Year: 2018, Page(s):929 - 940
Cited by:  Papers (4)
| | PDF (1717 KB) | HTML Media

Automated surface inspection (ASI) is a challenging task in industry, as collecting training dataset is usually costly and related methods are highly dataset-dependent. In this paper, a generic approach that requires small training data for ASI is proposed. First, this approach builds classifier on the features of image patches, where the features are transferred from a pretrained deep learning ne... View full abstract»

• ### Complex and Concurrent Negotiations for Multiple Interrelated e-Markets

Publication Year: 2013, Page(s):230 - 245
Cited by:  Papers (26)
| | PDF (1486 KB) | HTML

To date, most of the existing bargaining models are designed for supporting negotiation in only one market involving only two types of participants (buyers and sellers). This work devises a complex negotiation mechanism that supports negotiation activities among three types of participants in multiple interrelated markets. The complex negotiation mechanism consists of: 1) a bargaining-position-est... View full abstract»

• ### An Overview of Recent Advances in Event-Triggered Consensus of Multiagent Systems

Publication Year: 2018, Page(s):1110 - 1123
Cited by:  Papers (13)
| | PDF (863 KB) | HTML

Event-triggered consensus of multiagent systems (MASs) has attracted tremendous attention from both theoretical and practical perspectives due to the fact that it enables all agents eventually to reach an agreement upon a common quantity of interest while significantly alleviating utilization of communication and computation resources. This paper aims to provide an overview of recent advances in e... View full abstract»

• ### Recent Development in Big Data Analytics for Business Operations and Risk Management

Publication Year: 2017, Page(s):81 - 92
Cited by:  Papers (27)
| | PDF (2236 KB) | HTML

“Big data” is an emerging topic and has attracted the attention of many researchers and practitioners in industrial systems engineering and cybernetics. Big data analytics would definitely lead to valuable knowledge for many organizations. Business operations and risk management can be a beneficiary as there are many data collection channels in the related industrial systems (e.g., wireless sensor... View full abstract»

• ### Finite-Time Adaptive Control for a Class of Nonlinear Systems With Nonstrict Feedback Structure

Publication Year: 2018, Page(s):2774 - 2782
Cited by:  Papers (1)
| | PDF (1116 KB) | HTML

This paper focuses on finite-time adaptive neural tracking control for nonlinear systems in nonstrict feedback form. A semiglobal finite-time practical stability criterion is first proposed. Correspondingly, the finite-time adaptive neural control strategy is given by using this criterion. Unlike the existing results on adaptive neural/fuzzy control, the proposed adaptive neural controller guarant... View full abstract»

• ### Efficient Nondomination Level Update Method for Steady-State Evolutionary Multiobjective Optimization

Publication Year: 2017, Page(s):2838 - 2849
Cited by:  Papers (3)
| | PDF (1466 KB) | HTML Media

Nondominated sorting (NDS), which divides a population into several nondomination levels (NDLs), is a basic step in many evolutionary multiobjective optimization (EMO) algorithms. It has been widely studied in a generational evolution model, where the environmental selection is performed after generating a whole population of offspring. However, in a steady-state evolution model, where a populatio... View full abstract»

• ### Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints

Publication Year: 2016, Page(s):620 - 629
Cited by:  Papers (321)
| | PDF (1536 KB) | HTML

This paper studies the tracking control problem for an uncertain ${n}$ -link robot with full-state constraints. The rigid robotic manipulator is described as a multiinput and multioutput system. Adaptive neural network (NN) control for the robotic system with full-state constraints is designed. In the control design, the adaptive NNs are adopted to handle system uncertainties and disturbances. The... View full abstract»

• ### Interrelationship-Based Selection for Decomposition Multiobjective Optimization

Publication Year: 2015, Page(s):2076 - 2088
Cited by:  Papers (46)
| | PDF (1477 KB) | HTML

Multiobjective evolutionary algorithm based on decomposition (MOEA/D), which bridges the traditional optimization techniques and population-based methods, has become an increasingly popular framework for evolutionary multiobjective optimization. It decomposes a multiobjective optimization problem (MOP) into a number of optimization subproblems. Each subproblem is handled by an agent in a collabora... View full abstract»

• ### Event-Triggered Distributed Control of Nonlinear Interconnected Systems Using Online Reinforcement Learning With Exploration

Publication Year: 2018, Page(s):2510 - 2519
Cited by:  Papers (1)
| | PDF (4082 KB) | HTML Media

In this paper, a distributed control scheme for an interconnected system composed of uncertain input affine nonlinear subsystems with event triggered state feedback is presented by using a novel hybrid learning scheme-based approximate dynamic programming with online exploration. First, an approximate solution to the Hamilton-Jacobi-Bellman equation is generated with event sampled neural network (... View full abstract»

• ### Simulating Kinect Infrared and Depth Images

Publication Year: 2016, Page(s):3018 - 3031
Cited by:  Papers (7)
| | PDF (2736 KB) | HTML

With the emergence of the Microsoft Kinect sensor, many developer communities and research groups have found countless uses and have already published a wide variety of papers that utilize the raw depth images for their specific goals. New methods and applications that use the device generally require an appropriately large ensemble of data sets with accompanying ground truth for testing purposes,... View full abstract»

• ### Semi-Supervised and Unsupervised Extreme Learning Machines

Publication Year: 2014, Page(s):2405 - 2417
Cited by:  Papers (233)
| | PDF (1976 KB) | HTML

Extreme learning machines (ELMs) have proven to be efficient and effective learning mechanisms for pattern classification and regression. However, ELMs are primarily applied to supervised learning problems. Only a few existing research papers have used ELMs to explore unlabeled data. In this paper, we extend ELMs for both semi-supervised and unsupervised tasks based on the manifold regularization,... View full abstract»

• ### Graph Learning for Multiview Clustering

Publication Year: 2018, Page(s):2887 - 2895
Cited by:  Papers (1)
| | PDF (1466 KB) | HTML

Most existing graph-based clustering methods need a predefined graph and their clustering performance highly depends on the quality of the graph. Aiming to improve the multiview clustering performance, a graph learning-based method is proposed to improve the quality of the graph. Initial graphs are learned from data points of different views, and the initial graphs are further optimized with a ran... View full abstract»

• ### Event-Triggered Consensus of Homogeneous and Heterogeneous Multiagent Systems With Jointly Connected Switching Topologies

Publication Year: 2018, Page(s):1 - 10
| | PDF (869 KB)

This paper investigates the distributed event-based consensus problem of switching networks satisfying the jointly connected condition. Both the state consensus of homogeneous linear networks and the output consensus of heterogeneous networks are studied. Two kinds of event-based protocols based on local sampled information are designed, without the need to solve any matrix equation or inequality.... View full abstract»

• ### Cross-Modal Retrieval With CNN Visual Features: A New Baseline

Publication Year: 2017, Page(s):449 - 460
Cited by:  Papers (21)
| | PDF (2541 KB) | HTML

Recently, convolutional neural network (CNN) visual features have demonstrated their powerful ability as a universal representation for various recognition tasks. In this paper, cross-modal retrieval with CNN visual features is implemented with several classic methods. Specifically, off-the-shelf CNN visual features are extracted from the CNN model, which is pretrained on ImageNet with more than o... View full abstract»

• ### Optimized Assistive Human–Robot Interaction Using Reinforcement Learning

Publication Year: 2016, Page(s):655 - 667
Cited by:  Papers (26)
| | PDF (1451 KB) | HTML

An intelligent human-robot interaction (HRI) system with adjustable robot behavior is presented. The proposed HRI system assists the human operator to perform a given task with minimum workload demands and optimizes the overall human-robot system performance. Motivated by human factor studies, the presented control structure consists of two control loops. First, a robot-specific neuro-adaptive con... View full abstract»

• ### Some Necessary and Sufficient Conditions for Synchronization of Second-Order Interconnected Networks

Publication Year: 2018, Page(s):1 - 9
| | PDF (1047 KB)

This paper presents some necessary and sufficient conditions for the synchronization of second-order interconnected networks, where fixed inner-linked connections with information communication exist. First, a novel derivation of the conditions for a second-order polynomial with complex coefficients to be Hurwitz is provided. Based on this, a sufficient and necessary condition is proposed for the ... View full abstract»

• ### NOSEP: Nonoverlapping Sequence Pattern Mining With Gap Constraints

Publication Year: 2018, Page(s):2809 - 2822
Cited by:  Papers (1)
| | PDF (2254 KB) | HTML

Sequence pattern mining aims to discover frequent subsequences as patterns in a single sequence or a sequence database. By combining gap constraints (or flexible wildcards), users can specify special characteristics of the patterns and discover meaningful subsequences suitable for their own application domains, such as finding gene transcription sites from DNA sequences or discovering patterns for... View full abstract»

• ### A Learning-Based Hierarchical Control Scheme for an Exoskeleton Robot in Human-Robot Cooperative Manipulation

Publication Year: 2018, Page(s):1 - 3
| | PDF (2229 KB)

Exoskeleton robots can assist humans to perform activities of daily living with little effort. In this paper, a hierarchical control scheme is presented which enables an exoskeleton robot to achieve cooperative manipulation with humans. The control scheme consists of two layers. In low-level control of the upper limb exoskeleton robot, an admittance control scheme with an asymmetric barrier Lyapun... View full abstract»

• ### Fuzzy Broad Learning System: A Novel Neuro-Fuzzy Model for Regression and Classification

Publication Year: 2018, Page(s):1 - 11
| | PDF (1942 KB)

A novel neuro-fuzzy model named fuzzy broad learning system (BLS) is proposed by merging the Takagi-Sugeno (TS) fuzzy system into BLS. The fuzzy BLS replaces the feature nodes of BLS with a group of TS fuzzy subsystems, and the input data are processed by each of them. Instead of aggregating the outputs of fuzzy rules produced by every fuzzy subsystem into one value immediately, all of them are se... View full abstract»

• ### Time-Delay Neural Network for Continuous Emotional Dimension Prediction From Facial Expression Sequences

Publication Year: 2016, Page(s):916 - 929
Cited by:  Papers (18)
| | PDF (1551 KB) | HTML

Automatic continuous affective state prediction from naturalistic facial expression is a very challenging research topic but very important in human-computer interaction. One of the main challenges is modeling the dynamics that characterize naturalistic expressions. In this paper, a novel two-stage automatic system is proposed to continuously predict affective dimension values from facial expressi... View full abstract»

• ### Stacked Convolutional Denoising Auto-Encoders for Feature Representation

Publication Year: 2017, Page(s):1017 - 1027
Cited by:  Papers (59)
| | PDF (1793 KB) | HTML

Deep networks have achieved excellent performance in learning representation from visual data. However, the supervised deep models like convolutional neural network require large quantities of labeled data, which are very expensive to obtain. To solve this problem, this paper proposes an unsupervised deep network, called the stacked convolutional denoising auto-encoders, which can map images to hi... View full abstract»

• ### A Micro-GA Embedded PSO Feature Selection Approach to Intelligent Facial Emotion Recognition

Publication Year: 2017, Page(s):1496 - 1509
Cited by:  Papers (18)
| | PDF (1816 KB) | HTML

This paper proposes a facial expression recognition system using evolutionary particle swarm optimization (PSO)-based feature optimization. The system first employs modified local binary patterns, which conduct horizontal and vertical neighborhood pixel comparison, to generate a discriminative initial facial representation. Then, a PSO variant embedded with the concept of a micro genetic algorithm... View full abstract»

• ### Coupled Deep Autoencoder for Single Image Super-Resolution

Publication Year: 2017, Page(s):27 - 37
Cited by:  Papers (49)
| | PDF (2528 KB) | HTML

Sparse coding has been widely applied to learning-based single image super-resolution (SR) and has obtained promising performance by jointly learning effective representations for low-resolution (LR) and high-resolution (HR) image patch pairs. However, the resulting HR images often suffer from ringing, jaggy, and blurring artifacts due to the strong yet ad hoc assumptions that the LR image patch r... View full abstract»

• ### Locally Weighted Ensemble Clustering

Publication Year: 2018, Page(s):1460 - 1473
Cited by:  Papers (3)
| | PDF (2654 KB) | HTMLCode

Due to its ability to combine multiple base clusterings into a probably better and more robust clustering, the ensemble clustering technique has been attracting increasing attention in recent years. Despite the significant success, one limitation to most of the existing ensemble clustering methods is that they generally treat all base clusterings equally regardless of their reliability, which make... View full abstract»

• ### Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach

Publication Year: 2013, Page(s):1656 - 1671
Cited by:  Papers (213)
| | PDF (1260 KB) | HTML

Classification problems often have a large number of features in the data sets, but not all of them are useful for classification. Irrelevant and redundant features may even reduce the performance. Feature selection aims to choose a small number of relevant features to achieve similar or even better classification performance than using all features. It has two main conflicting objectives of maxim... View full abstract»

• ### Cooperative Robots to Observe Moving Targets: Review

Publication Year: 2018, Page(s):187 - 198
Cited by:  Papers (6)
| | PDF (1114 KB) | HTML

The deployment of multiple robots for achieving a common goal helps to improve the performance, efficiency, and/or robustness in a variety of tasks. In particular, the observation of moving targets is an important multirobot application that still exhibits numerous open challenges, including the effective coordination of the robots. This paper reviews control techniques for cooperative mobile robo... View full abstract»

• ### Trajectory Predictor by Using Recurrent Neural Networks in Visual Tracking

Publication Year: 2017, Page(s):3172 - 3183
Cited by:  Papers (3)
| | PDF (1534 KB) | HTML

Motion models have been proved to be a crucial part in the visual tracking process. In recent trackers, particle filter and sliding windows-based motion models have been widely used. Treating motion models as a sequence prediction problem, we can estimate the motion of objects using their trajectories. Moreover, it is possible to transfer the learned knowledge from annotated trajectories to new ob... View full abstract»

• ### Consensus of Linear Multi-Agent Systems by Distributed Event-Triggered Strategy

Publication Year: 2016, Page(s):148 - 157
Cited by:  Papers (137)
| | PDF (1008 KB) | HTML

This paper studies the consensus problem of multi-agent systems with general linear dynamics. We propose a novel event-triggered control scheme with some desirable features, namely, distributed, asynchronous, and independent. It is shown that consensus of the controlled multi-agent system can be reached asymptotically. The feasibility of the event-triggered strategy is further verified by the excl... View full abstract»

• ### Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking

Publication Year: 2017, Page(s):4014 - 4024
Cited by:  Papers (9)
| | PDF (1171 KB) | HTML

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. T... View full abstract»

• ### Network-Based T–S Fuzzy Dynamic Positioning Controller Design for Unmanned Marine Vehicles

Publication Year: 2018, Page(s):2750 - 2763
| | PDF (1960 KB) | HTML

This paper is concerned with a Takagi-Sugeno (T-S) fuzzy dynamic positioning controller design for an unmanned marine vehicle (UMV) in network environments. Network-based T-S fuzzy dynamic positioning system (DPS) models for the UMV are first established. Then, stability and stabilization criteria are derived by taking into consideration an asynchronous difference between the normalized membership... View full abstract»

• ### Distributed Task Rescheduling With Time Constraints for the Optimization of Total Task Allocations in a Multirobot System

Publication Year: 2018, Page(s):2583 - 2597
| | PDF (1358 KB) | HTML Media

This paper considers the problem of maximizing the number of task allocations in a distributed multirobot system under strict time constraints, where other optimization objectives need also be considered. It builds upon existing distributed task allocation algorithms, extending them with a novel method for maximizing the number of task assignments. The fundamental idea is that a task assignment to... View full abstract»

• ### A Piecewise-Markovian Lyapunov Approach to Reliable Output Feedback Control for Fuzzy-Affine Systems With Time-Delays and Actuator Faults

Publication Year: 2018, Page(s):2723 - 2735
Cited by:  Papers (1)
| | PDF (978 KB) | HTML

This paper addresses the problem of delaydependent robust and reliable H∞static output feedback (SOF) control for a class of uncertain discrete-time Takagi-Sugeno fuzzy-affine (FA) systems with time-varying delay and actuator faults in a singular system framework. The Markov chain is employed to describe the actuator faults behaviors. In particular, by utilizing a system augmentation ap... View full abstract»

• ### Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images

Publication Year: 2018, Page(s):16 - 28
Cited by:  Papers (10)
| | PDF (4476 KB) | HTML

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial ... View full abstract»

• ### Adaptive Critic Nonlinear Robust Control: A Survey

Publication Year: 2017, Page(s):3429 - 3451
Cited by:  Papers (7)
| | PDF (1954 KB) | HTML

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and s... View full abstract»

• ### A Distributed Dynamic Event-Triggered Control Approach to Consensus of Linear Multiagent Systems With Directed Networks

Publication Year: 2018, Page(s):1 - 6
| | PDF (701 KB)

In this paper, we study the consensus problem for a class of linear multiagent systems, where the communication networks are directed. First, a dynamic event-triggering mechanism is introduced, including some existing static event-triggering mechanisms as its special cases. Second, based on the dynamic event-triggering mechanism, a distributed control protocol is developed, which ensures that all ... View full abstract»

• ### Observer-Based Event-Triggering Consensus Control for Multiagent Systems With Lossy Sensors and Cyber-Attacks

Publication Year: 2017, Page(s):1936 - 1947
Cited by:  Papers (13)
| | PDF (785 KB) | HTML

In this paper, the observer-based event-triggering consensus control problem is investigated for a class of discrete-time multiagent systems with lossy sensors and cyber-attacks. A novel distributed observer is proposed to estimate the relative full states and the estimated states are then used in the feedback protocol in order to achieve the overall consensus. An event-triggered mechanism with st... View full abstract»

• ### Adaptive Neural Network Control for Robotic Manipulators With Unknown Deadzone

Publication Year: 2018, Page(s):2670 - 2682
| | PDF (2652 KB) | HTML

This paper addresses the problem of robotic manipulators with unknown deadzone. In order to tackle the uncertainty and the unknown deadzone effect, we introduce adaptive neural network (NN) control for robotic manipulators. State-feedback control is introduced first and a high-gain observer is then designed to make the proposed control scheme more practical. One radial basis function NN (RBFNN) is... View full abstract»

• ### An Efficient Method for Traffic Sign Recognition Based on Extreme Learning Machine

Publication Year: 2017, Page(s):920 - 933
Cited by:  Papers (36)
| | PDF (2300 KB) | HTML

This paper proposes a computationally efficient method for traffic sign recognition (TSR). This proposed method consists of two modules: (1) extraction of histogram of oriented gradient variant (HOGv) feature and (2) a single classifier trained by extreme learning machine (ELM) algorithm. The presented HOGv feature keeps a good balance between redundancy and local details such that it can represen... View full abstract»

• ### Finite Time Fault Tolerant Control for Robot Manipulators Using Time Delay Estimation and Continuous Nonsingular Fast Terminal Sliding Mode Control

Publication Year: 2017, Page(s):1681 - 1693
Cited by:  Papers (31)
| | PDF (1480 KB) | HTML

In this paper, a novel finite time fault tolerant control (FTC) is proposed for uncertain robot manipulators with actuator faults. First, a finite time passive FTC (PFTC) based on a robust nonsingular fast terminal sliding mode control (NFTSMC) is investigated. Be analyzed for addressing the disadvantages of the PFTC, an AFTC are then investigated by combining NFTSMC with a simple fault diagnosis ... View full abstract»

• ### Genetic Learning Particle Swarm Optimization

Publication Year: 2016, Page(s):2277 - 2290
Cited by:  Papers (52)
| | PDF (3242 KB) | HTML Media

Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is ... View full abstract»

• ### Automatic Facial Expression Recognition System Using Deep Network-Based Data Fusion

Publication Year: 2018, Page(s):103 - 114
Cited by:  Papers (3)
| | PDF (1661 KB) | HTML Media

This paper presents a novel automatic facial expressions recognition system (AFERS) using the deep network framework. The proposed AFERS consists of four steps: 1) geometric features extraction; 2) regional local binary pattern (LBP) features extraction; 3) fusion of both the features using autoencoders; and 4) classification using Kohonen self-organizing map (SOM)-based classifier. This paper mak... View full abstract»

• ### Clustering by Local Gravitation

Publication Year: 2018, Page(s):1383 - 1396
| | PDF (1441 KB) | HTML

The objective of cluster analysis is to partition a set of data points into several groups based on a suitable distance measure. We first propose a model called local gravitation among data points. In this model, each data point is viewed as an object with mass, and associated with a local resultant force (LRF) generated by its neighbors. The motivation of this paper is that there exist distinct d... View full abstract»

• ### Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems

Publication Year: 2016, Page(s):1591 - 1601
Cited by:  Papers (110)
| | PDF (949 KB) | HTML

Combined with backstepping techniques, an observer-based adaptive consensus tracking control strategy is developed for a class of high-order nonlinear multiagent systems, of which each follower agent is modeled in a semi-strict-feedback form. By constructing the neural network-based state observer for each follower, the proposed consensus control method solves the unmeasurable state problem of hig... View full abstract»

• ### Automatic Leader-Follower Persistent Formation Generation With Minimum Agent-Movement in Various Switching Topologies

Publication Year: 2018, Page(s):1 - 13
| | PDF (1395 KB)

This paper presents the generation strategy, motion planning, and switching topologies of a distance-based leader-follower relation-invariable persistent formation (RIPF) of multiagent systems (MASs). An efficient algorithm is designed to find out if a persistent formation can be generated from a rigid graph. Derived from the properties of a rigid graph, the algorithm to generate RIPF from any ini... View full abstract»

• ### The Analysis of Image Contrast: From Quality Assessment to Automatic Enhancement

Publication Year: 2016, Page(s):284 - 297
Cited by:  Papers (96)
| | PDF (2596 KB) | HTML

Proper contrast change can improve the perceptual quality of most images, but it has largely been overlooked in the current research of image quality assessment (IQA). To fill this void, we in this paper first report a new large dedicated contrast-changed image database (CCID2014), which includes 655 images and associated subjective ratings recorded from 22 inexperienced observers. We then present... View full abstract»

• ### Supervised and Unsupervised Aspect Category Detection for Sentiment Analysis with Co-occurrence Data

Publication Year: 2018, Page(s):1263 - 1275
Cited by:  Papers (1)
| | PDF (1393 KB) | HTML

Using online consumer reviews as electronic word of mouth to assist purchase-decision making has become increasingly popular. The Web provides an extensive source of consumer reviews, but one can hardly read all reviews to obtain a fair evaluation of a product or service. A text processing framework that can summarize reviews, would therefore be desirable. A subtask to be performed by such a frame... View full abstract»

• ### Simultaneous Observation of Hybrid States for Cyber-Physical Systems: A Case Study of Electric Vehicle Powertrain

Publication Year: 2018, Page(s):2357 - 2367
Cited by:  Papers (11)
| | PDF (1572 KB) | HTML

As a typical cyber-physical system (CPS), electrified vehicle becomes a hot research topic due to its high efficiency and low emissions. In order to develop advanced electric powertrains, accurate estimations of the unmeasurable hybrid states, including discrete backlash nonlinearity and continuous half-shaft torque, are of great importance. In this paper, a novel estimation algorithm for simultan... View full abstract»

• ### Recurrent Broad Learning Systems for Time Series Prediction

Publication Year: 2018, Page(s):1 - 13
| | PDF (2587 KB)

The broad learning system (BLS) is an emerging approach for effective and efficient modeling of complex systems. The inputs are transferred and placed in the feature nodes, and then sent into the enhancement nodes for nonlinear transformation. The structure of a BLS can be extended in a wide sense. Incremental learning algorithms are designed for fast learning in broad expansion. Based on the typi... View full abstract»

• ### FUIQA: Fetal Ultrasound Image Quality Assessment With Deep Convolutional Networks

Publication Year: 2017, Page(s):1336 - 1349
Cited by:  Papers (6)
| | PDF (2746 KB) | HTML

The quality of ultrasound (US) images for the obstetric examination is crucial for accurate biometric measurement. However, manual quality control is a labor intensive process and often impractical in a clinical setting. To improve the efficiency of examination and alleviate the measurement error caused by improper US scanning operation and slice selection, a computerized fetal US image quality as... 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