A new algorithm for OFDM joint data detection and phase noise cancellation

This paper proposes a new iterative algorithm for OFDM joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the problem of "overfitting" such that the iterative approach may converge to a trivial solution. Although it is essential for this joint approach, the overfitting problem was relatively less studied in existing algorithms. In this paper, specifically, we apply a hard decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the phase noise, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical simulations are also given to verify the proposed algorithm.

Design of redundant drive joint with adjustable stiffness and damping mechanism to improve joint admittance

Improving admittance of robotic joints is the key issue for making rehabilitation robots safe. This paper describes a design of Redundant Drive Joint (RD-Joint) which allows greater flexibility in the design of robotic mechanisms. The design strategy of the RD-Joint employs a systematic approach which consists of 1) adopting a redundant joint mechanism with internal kinematical redundancy to reduce effective joint inertia, and 2) adopting an adjustable admittance mechanism with a novel Cross link Reduction Mechanism and mechanical springs and dampers as a passive second actuator. First, the basic concepts used to construct the redundant drive joint mechanism are explained, in particular the method that allows a reduction in effective inertia at the output joint. The basic structure of the RD-Joint is introduced based on the idea of reduced inertia along with a method to include effective stiffness and damping. Then, the basic design of the adjustable admittance mechanism is described. Finally, a prototype of RD-joint is described and its expected characteristics are discussed.

Proposal of an admittance enhanced redundant joint mechanism to improve backdrivability

This paper describes a proposed admittance enhanced redundant joint mechanism (AERJM) which allows greater flexibility in the design of robotic joints. First, the basic concept of a redundant joint mechanism that reduces joint inertia is explained. Second, the AERJM structure is discussed. AERJM consists of a redundancy introducing mechanism (RIM), the adjustable admittance mechanism (AAM) and an admittance enhancing actuator. The working principles of the AERJM concept are analysed. The design and a working prototype, consisting of a variable reduction mechanism, along with a spring and a damper with constant coefficients, are described.

OFDM joint data detection and phase noise cancellation based on minimum mean square prediction error

This paper proposes a new iterative algorithm for orthogonal frequency division multiplexing (OFDM) joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the relatively less studied problem of "overfitting" such that the iterative approach may converge to a trivial solution. Specifically, we apply a hard-decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the PHN, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical Simulations are also given to verify the proposed algorithm. (C) 2008 Elsevier B.V. All rights reserved.

OFDM joint data detection and phase noise cancellation for constant modulus modulations

This correspondence proposes a new algorithm for the OFDM joint data detection and phase noise (PHN) cancellation for constant modulus modulations. We highlight that it is important to address the overfitting problem since this is a major detrimental factor impairing the joint detection process. In order to attack the overfitting problem we propose an iterative approach based on minimum mean square prediction error (MMSPE) subject to the constraint that the estimated data symbols have constant power. The proposed constrained MMSPE algorithm (C-MMSPE) significantly improves the performance of existing approaches with little extra complexity being imposed. Simulation results are also given to verify the proposed algorithm.

Dynamic modulation of human motor activity when observing actions

Previous studies have demonstrated that when we observe somebody else executing an action many areas of our own motor systems are active. It has been argued that these motor activations are evidence that we motorically simulate observed actions; this motoric simulation may support various functions such as imitation and action understanding. However, whether motoric simulation is indeed the function of motor activations during action observation is controversial, due to inconsistency in findings. Previous studies have demonstrated dynamic modulations in motor activity when we execute actions. Therefore, if we do motorically simulate observed actions, our motor systems should also be modulated dynamically, and in a corresponding fashion, during action observation. Using magnetoencephalography (MEG), we recorded the cortical activity of human participants while they observed actions performed by another person. Here, we show that activity in the human motor system is indeed modulated dynamically during action observation. The finding that activity in the motor system is modulated dynamically when observing actions can explain why studies of action observation using functional magnetic resonance imaging (fMRI) have reported conflicting results, and is consistent with the hypothesis that we motorically simulate observed actions.

Methods for kinematic modeling of biological and robotic systems

The main objective is to develop methods that automatically generate kinematic models for the movements of biological and robotic systems. Two methods for the identification of the kinematics are presented. The first method requires the elimination of the displacement variables that cannot be measured while the second method attempts to estimate the changes in these variables. The methods were tested using a planar two-revolute-joint linkage. Results show that the model parameters obtained agree with the actual parameters to within 5%. Moreover, the methods were applied to model head and neck movements in the sagittal plane. The results indicate that these movements are well modeled by a two-revolute-joint system. A spatial three-revolute-joint model was also discussed and tested.

Kinematic modeling of head-neck movements

The main objective is to generate kinematic models for the head and neck movements. The motivation comes from our study of individuals with quadriplegia and the need to design rehabilitation aiding devices such as robots and teletheses that can be controlled by head-neck movements. It is then necessary to develop mathematical models for the head and neck movements. Two identification methods have been applied to study the kinematics of head-neck movements of able-body as well as neck-injured subjects. In particular, sagittal plane movements are well modeled by a planar two-revolute-joint linkage. In fact, the motion in joint space seems to indicate that sagittal plane movements may be classified as a single DOF motion. Finally, a spatial three-revolute-joint system has been employed to model 3D head-neck movements.

Numerical modeling of inhaled charged aerosol deposition in human airways

A new numerical modeling of inhaled charge aerosol has been developed based on a modified Weibel's model. Both the velocity profiles (slug and parabolic flows) and the particle distributions (uniform and parabolic distributions) have been considered. Inhaled particles are modeled as a dilute dispersed phase flow in which the particle motion is controlled by fluid force and external forces acting on particles. This numerical study extends the previous numerical studies by considering both space- and image-charge forces. Because of the complex computation of interacting forces due to space-charge effect, the particle-mesh (PM) method is selected to calculate these forces. In the PM technique, the charges of all particles are assigned to the space-charge field mesh, for calculating charge density. The Poisson's equation of the electrostatic potential is then solved, and the electrostatic force acting on individual particle is interpolated. It is assumed that there is no effect of humidity on charged particles. The results show that many significant factors also affect the deposition, such as the volume of particle cloud, the velocity profile and the particle distribution. This study allows a better understanding of electrostatic mechanism of aerosol transport and deposition in human airways.

Joint modelling of obstacle induced and mesoscale changes: current limits and challenges

Obstacles considerably influence boundary layer processes. Their influences have been included in mesoscale models (MeM) for a long time. Methods used to parameterise obstacle effects in a MeM are summarised in this paper using results of the mesoscale model METRAS as examples. Besides the parameterisation of obstacle influences it is also possible to use a joint modelling approach to describe obstacle induced and mesoscale changes. Three different methods may be used for joint modelling approaches: The first method is a time-slice approach, where steady basic state profiles are used in an obstacle resolving microscale model (MiM, example model MITRAS) and diurnal cycles are derived by joining steady-state MITRAS results. The second joint modelling approach is one-way nesting, where the MeM results are used to initialise the MiM and to drive the boundary values of the MiM dependent on time. The third joint modelling approach is to apply multi-scale models or two-way nesting approaches, which include feedbacks from the MiM to the MeM. The advantages and disadvantages of the different approaches and remaining problems with joint Reynolds-averaged Navier–Stokes modelling approaches are summarised in the paper.