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In this paper, we present a method to reconstruct the configurations of kinematic trees of rigid bodies not using measurements of relative angles (such as, e.g. rotary encoders at joints) but absolute posture sensors (such as IMUs) along with suitable filter algorithms. We argue that the relatively larger inaccuracies shown by absolute sensors can be compensated by suitable processing, such as a passive...
This paper introduces a Sensor Array System for the 3D capture and representation of users' limb and body movements. It also develops a design and implementation of a Wireless Inertial Measurement Unit (IMU) Sensor Array. By placing sensors on one's arm, hand, upper leg and lower leg, data needed by the application developers to represent the body pose of the user in a virtual environment is provided...
The article contains practical algorithm for the adaptive Bayesian approach to the synthesis of algorithms for joint detection-estimation using multi-channel and adaptive schemes for joint detection-estimation.
The correct way to design controllers for dynamic robots is still very much an open question. This is in a large part due to the complexity and uncertainty in modeling their nonlinear dynamics. In this work, we focus on deriving concise dynamic expressions for a particular class of robots that can be used to better reduce uncertainty with respect to unknown parameters in realtime. We accomplish this...
In this paper, we focus on the theoretical localization accuracy of two localization algorithms in noncoherent MIMO radar systems with widely separated antennas. The first one is the optimal method for multitarget localization which is simply to expand the dimension of the parameter vector and thus perform a global maximum of the joint likelihood function of all the targets. The second one is a suboptimal...
For using industrial robots in applications where the robot physically interacts with the environment, such as assembly, force control is usually needed. A force sensor may, however, be expensive and add mass to the system. An alternative is therefore to estimate the external force using the motor torques. This paper considers the problem of force estimation for the case when the robot is not moving,...
We investigate cooperative in-band radar and communications signaling for frequency-modulated continuous-wave (FMCW) radar and Doppler estimation. While each system typically considers the other system a source of interference, by considering the radar and communications operations to be a single system, joint performance bounds can be formulated. We extend previous work where a novel estimation and...
This paper presents a new approach to high speed visual servoing in the case of a 6 DOF industrial manipulator that takes into account the dynamics of the manipulator in the synthesis of the visual controller. The manipulator with its actuators (DC motors), their current feedback loops and their velocity control loops, is modelled as a "virtual Cartesian motion device". A linearized model...
A method for joint estimation of wireless communication channels to multiple users utilizing pulse shaping knowledge is presented. The pulse shaping in the transmitter and the receiver is incorporated into the channel estimation by approximating it with a set of pulse shaping functions. In joint multi-user channel estimation the number of parameters to be estimated grows linearly with the number of...
In this paper, the general formula of disparity estimation based on Bayesian Maximum A Posteriori (MAP) algorithm is derived and implemented with simplified probabilistic models. The probabilistic models are independence and similarity among the neighboring disparities in the configuration. The formula can be implemented into the some different forms corresponding to the probabilistic models in the...
Composite signals are nonstationary processes consisting of trend, noise and cyclic components. A cyclic component consists of periodic or almost periodic data. In this paper we present a method based on nonlinear order statistics that evaluates the fundamental period of a cyclic component. This information can be used for decomposition of composite signals.
This paper addresses the problem of blind deconvolution for ultrasound images within a Bayesian framework. The prior of the unknown ultrasound image to be estimated is assumed to be a product of generalized Gaussian distributions. The point spread function of the system is also assumed to be unknown and is assigned a Gaussian prior distribution. These priors are combined with the likelihood function...
Operator self-similarity naturally extends the concepts of univariate self-similarity and scale invariance to multivariate data. Beyond a vector of Hurst parameters, operator self-similarity models also involve a mixing matrix. The present contribution aims at estimating the collection of Hurst parameters in the case where the mixing matrix is not diagonal. To the best of our knowledge, this has never...
This paper presents a new method to jointly estimate the spherical harmonic coefficients for all the voxels from noisy magnitude diffusion-weighted images acquired in high angular resolution diffusion imaging. The proposed method uses a penalized maximum likelihood estimation formulation that integrates a noncentral χ distribution based noisy data model, a sparsity promoting penalty on the spherical...
The problem of threshold performance improvement of direction finding using estimator bank approach is considered. The modified unitary Root-MUSIC estimator and pseudo-noise resampling are used to form the estimator bank. The classification of roots of the modified unitary Root-MUSIC polynomial based on their proximity to the unit circle is used on the final step of proposed approach.
In single-channel speech enhancement the spectral amplitude of the noisy signal is often modified while the noisy spectral phase is directly employed for signal reconstruction. Recently, additional improvement in speech enhancement performance has been reported when the noisy phase is modified. In this work, we propose a Bayesian estimator for phase of harmonics given the noisy speech. The proposed...
This paper presents a Bayesian algorithm for linear spectral unmixing that accounts for outliers present in the data. The proposed model assumes that the pixel reflectances are linear mixtures of unknown endmembers, corrupted by an additional term modelling outliers and additive Gaussian noise. A Markov random field is considered for outlier detection based on the spatial and spectral structures of...
This paper extends the use of coprime arrays and samplers for the case of moving sources. Space-time adaptive processing (STAP) plays an important role in estimating direction-of-arrivals (DOAs) and radial velocities of emitting sources. However, the detection performance is fundamentally limited by the array geometry and the temporal samplers at each sensor. Coprime arrays and coprime samplers offer...
Audio thumbnailing, which aims at finding the most representative audio segment of a music recording, is an important task in music information retrieval. In general, the notion of a thumbnail is not well-defined and several musical parts may be good thumbnail candidates. For example, for popular music, both a verse and a refrain section may serve as suitable thumbnail candidates. Instead of considering...
In this paper, our aim is to investigate the control of bias accumulation when estimating mutual information from nearest neighbors non-parametric approach with continuously distributed random data. Using a multidimensional Taylor series expansion, a general relationship between the estimation bias and neighborhood size for plug-in entropy estimator is established without any assumption on the data...
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