The rhythms of steady posture
Beta-band (15-30Hz) oscillations in motor cortex have been implicated in voluntary movement and postural control. Yet the mechanisms linking those oscillations to function remains elusive. Recently, spatial waves of synchronized beta oscillations have ...
Minimum connected component - A novel approach to detection of cognitive load induced changes in functional brain networks
Recent advances in computational neuroscience have enabled trans-disciplinary researchers to address challenging tasks such as the identification and characterization of cognitive function in the brain. The application of graph theory has contributed to ...
A heuristic branch-and-bound based thresholding algorithm for unveiling cognitive activity from EEG data
One of the biggest challenges in the field of computational neuroscience from the perspective of complex network analysis is the measurement of dynamic local and global interactions of the brain regions during cognitive function. Graph theoretic ...
A CPG system based on spiking neurons for hexapod robot locomotion
- H. Rostro-Gonzalez,
- P.A. Cerna-Garcia,
- G. Trejo-Caballero,
- C.H. Garcia-Capulin,
- M.A. Ibarra-Manzano,
- J.G. Avina-Cervantes,
- C. Torres-Huitzil
In this paper, we propose a locomotion system based on a central pattern generator (CPG) for a hexapod robot, suitable for embedded hardware implementation. The CPG system was built as a network of spiking neurons, which produce rhythmic signals for ...
Closed-loop control of a minimal central pattern generator network
Many central pattern generators (CPGs) are built on a basic circuit of reciprocally inhibitory neurons, the minimal configuration that can produce distinct rhythmic patterns for controlling antagonistic muscles. In this paper, we use a closed-loop to ...
Perception-driven adaptive CPG-based locomotion for hexapod robots
According to neurobiological studies, rhythmic motion in animals is controlled by neural circuits known as central pattern generators (CPGs), which are robust against transient perturbations. Yet, CPGs can integrate sensory feedback that potentially ...
Combining central pattern generators and reflexes
Locomotion of quadruped robots has not yet achieved the robustness, harmony, efficiency and flexibility of its biological counterparts. Biological evidences showed that there is a two-way interaction between the Central Pattern Generators (CPGs) and the ...
A computational model for ratbot locomotion based on cyborg intelligence
Ratbots with electric stimulation in their brains possess not only their own biological sensation, perception, memory, and locomotion control abilities, but also machine visual sensation, memory and computing functionalities. With electrodes implanted ...
Engineering central pattern generated behaviors for the deployment of robotic systems
In order to face with various contexts and situations, autonomous robots should be endowed with many different sensors and behaviors. These requirements pose new challenges such as the coordination of multiple parallel activities and the efficient use ...
Extending SMER-based CPGs to accommodate total support phases and kinematics-safe transitions between gait rhythms of hexapod robots
This work presents a new extension to the artificial CPGs (Central Pattern Generators) based on Scheduling by Multiple Edge Reversal (SMER) proposed by Yang and França. The insertion of a total support phase between each particular swing and support ...
A central pattern generator for controlling sequential activation in a neural architecture for sentence processing
The neural architecture for sentence processing is a model of a neural 'blackboard' capable of temporarily storing both semantic and syntactic information. Retrieving information from the neural blackboard requires a sequence of activations that is ...
Disturbance rejection of Central Pattern Generator based torque-stiffness-controlled dynamic walking
The concept of torque-stiffness-controlled dynamic walking expands the applicability of passivity-based bipeds while preserving energetic efficiency due to the addition of controllable stiffness. Central Pattern Generator (CPG) based approach introduces ...
Adaptive guidance system design for the assistive robotic walker
As seniors are the fastest growing populations in the world, walking assistive robots have recently received much attention. In this paper, we proposed an effective motion guidance system equipped upon a robotic walking assistant to emulate the ...
Evaluating Quantum Neural Network filtered motor imagery brain-computer interface using multiple classification techniques
The raw EEG signal acquired non-invasively from the sensorimotor cortex during the motor imagery (MI) performed by a brain-computer interface (BCI) user is naturally embedded with noise while the actual noise-free EEG is still unattainable. This paper ...
Reinforcement learning control for coordinated manipulation of multi-robots
In this paper, coordination control is investigated for multi-robots to manipulate an object with a common desired trajectory. Both trajectory tracking and control input minimization are considered for each individual robot manipulator, such that ...
Saliency generation from complex scene via digraph and Bayesian inference
Making a close inspection of the recent progress made in computer vision we will find that more and more advancement can be attributed to the introduction of bio-inspired algorithms, which is a flourishing area of computing. Biological patterns can be ...
A level set method with shape priors by using locality preserving projections
A novel level set method (LSM) with the constraint of shape priors is proposed to implement a selective image segmentation. Firstly, the shape priors are aligned by using image moment to deprive the spatial related information. Secondly, the aligned ...
Fast total-variation based image restoration based on derivative alternated direction optimization methods
The total variation (TV) model is one of the most successful methods for image restoration, as well as an ideal bed to develop optimization algorithms for solving sparse representation problems. Previous studies showed that derivative space formulation ...
Improve scene classification by using feature and kernel combination
Scene classification is an important issue in the computer vision field. In this paper, we propose an improved approach for scene classification. Compared with the previous work, the proposed approach has two processes to improve the performance of ...
A compressed sensing ensemble classifier with application to human detection
This paper proposes a novel Compressed Sensing Ensemble Classifier (CSEC) for human detection. The proposed CSEC employs the compressed sensing technique to get a more sparse model with a more reasonable selection of base classifiers. The major ...
Harmonious competition learning for Gaussian mixtures
This paper proposes a novel automatic model selection algorithm for learning Gaussian mixtures. Unlike EM, we shall further increase the negative entropy of the posterior of latent variables to exert an indirect effect on model selection. The increase ...
Combining multiple clusterings via crowd agreement estimation and multi-granularity link analysis
The clustering ensemble technique aims to combine multiple clusterings into a probably better and more robust clustering and has been receiving an increasing attention in recent years. There are mainly two aspects of limitations in the existing ...
A comparative study on selecting acoustic modeling units in deep neural networks based large vocabulary Chinese speech recognition
This paper compared the performance of different acoustic modeling units in deep neural networks (DNNs) based large vocabulary continuous speech recognition (LVCSR) systems for Chinese. Recently, the deep neural networks based acoustic modeling method ...
A hierarchical path planning approach based on A* and least-squares policy iteration for mobile robots
In this paper, we propose a novel hierarchical path planning approach for mobile robot navigation in complex environments. The proposed approach has a two-level structure. In the first level, the A* algorithm based on grids is used to find a geometric ...
Design of an autonomous intelligent Demand-Side Management system using stochastic optimisation evolutionary algorithms
Demand-Side Management systems aim to modulate energy consumption at the customer side of the meter using price incentives. Current incentive schemes allow consumers to reduce their costs, and from the point of view of the supplier play a role in load ...
Prediction of the Italian electricity price for smart grid applications
In this paper we address the problem of one day-ahead hourly electricity price forecast for smart grid applications. To this aim, we investigate the application of a number of predictive models for time-series, including methods based on empirical ...
