We introduce a joint decoding algorithm for a Huffman source code followed by a convolutional channel code. The algorithm incorporates a restriction to valid Huffman codewords into the convolutional code’s trellis. Performance is improved by this restriction. Furthermore, soft Huffman decoding is implicitly included, and a priori probabilities of input symbols can be easily exploited, if availa...

An arti...cial neural network model is used to predict the performance of Sino-foreign joint ventures. Performance of international joint ventures remains a relatively under-researched area, yet its importance is well recognized due to the tremendous surge in joint venture activities in the past decade. Data on 2,416 Sino-foreign joint ventures was gathered, allowing for empirical analysis usin...

In this paper, a method for suppressing residual vibrations in flexible payloads, carried by robot manipulators, is proposed and experimentally demonstrated. The proposed method is based on the preconditioning of the robot joint trajectories using FIR digital filters. Several classes of FIR filters such as: a) Parks-McClellan, b) Window-based methods (using Hamming, Hanning, Boxcar, Kaiser, Bar...

OBJECTIVE Powered robotic prostheses create a need for natural-feeling user interfaces and robust control schemes. Here, we examined the ability of a nonlinear autoregressive model to continuously map the kinematics of a transtibial prosthesis and electromyographic (EMG) activity recorded within socket to the future estimates of the prosthetic ankle angle in three transtibial amputees. APPROA...

Standard automatic speech recognition (ASR) systems follow a divide and conquer approach to convert speech into text. Alternately, the end goal is achieved by a combination of sub-tasks, namely, feature extraction, acoustic modeling and sequence decoding, which are optimized in an independent manner. More recently, in the machine learning community deep learning approaches have emerged which al...

this paper presents optimal control method to path planning of mobile robots with flexible joints. dynamic equations are derived and additional kinematic constraints are used to solve the extra dofs arose from base mobility. then with modeling the elasticity at each joint as a linear torsinal spring, the set of equations are formed. the hamiltonian function is formed and the necessary condition...

Deep multi-color galaxy surveys with photometric redshifts will provide a large number of twopoint correlation observables: galaxy-galaxy angular correlations, galaxy-shear cross correlations, and shear-shear correlations between all redshifts. These observables can potentially enable a joint determination of the dark energy dependent evolution of the dark matter and distances as well as the re...

BACKGROUND Measurement of individuals' costs and outcomes in randomized trials allows uncertainty about cost effectiveness to be quantified. Uncertainty is expressed as probabilities that an intervention is cost effective, and confidence intervals of incremental cost effectiveness ratios. Randomizing clusters instead of individuals tends to increase uncertainty but such data are often analysed ...

We study discriminative joint density models, that is, generative models for the joint density p(c,x) learned by maximizing a discriminative cost function, the conditional likelihood. We use the framework to derive generative models for generalized linear models, including logistic regression, linear discriminant analysis, and discriminative mixture of unigrams. The benefits of deriving the dis...