Wireless systems with multiple transmit and receive antennas (MIMO systems) provide high capacity due to the plurality of modes available in the channel. Previous code designs for MIMO systems have focused primarily on multiplexed signaling for high data rate or diversity signaling for high link reliability. In this paper, based on previous work reported in [1, 2], and using results from frame ...

The search for more running speed had brought an abundance of training methods and combinations thereof. However, the benefit to sprint improvement of these methods does not compare favourably against the value of sprint training itself for which sprint running has the exact specificity. The rapid dynamic training exercise in this experiment is intended to isolate the muscles that contract rapi...

This paper proposes a recognition structure designed for handling continuous speech in a natural and computationally efficient way. without the need for a higher Ievel algorithm (like. e.g .• Ievel building). This structure is based on a probabilistic state machine (PSM). but unlike Hidden Markov Models. the transition probabilities at each time frame depend on the observation made on the input...

This paper describes the training of a recurrent neural network as the letter posterior probability estimator for a hidden Markov model, off-line handwriting recognition system. The network estimates posterior distributions for each of a series of frames representing sections of a handwritten word. The supervised training algorithm, backpropagation through time, requires target outputs to be pr...

A common computational model in distributed embedded systems is that the nodes exchange signals via a network. Most often a signal represents the state of some physical device and has a signal size ranging from a single bit up to a few bytes. Furthermore, each signal typically has a deadline requirement. The communication networks used are often based on a broadcast bus where fixed or variable ...

In this paper we report on the combination of multilingual Hidden Markov Models for the recognition of non-native speech. Using a digit recognition task as an example, we first demonstrate the benefits of bilingual acoustic models that incorporate training data from both the target language and the speakers’ native language, and then compare two different recognizer combination methods, namely ...

This report describes the implementation of a discriminative HMM parameter estimation technique known as Frame Discrimination (FD) for large vocabulary speech recognition, and reports improvements in accuracy over ML-trained and MMI-trained models. Features of the implementation include the use of an algorithm called the Roadmap algorithm which selects the most important Gaussians for a given i...

In this paper, we proposed a novel efficient barbell trajectory extraction algorithm and further implemented a computer aided weightlifting training system with our proposed algorithm. The proposed method extracts the barbell trajectory from the video sequence both considering spatial and temporal information which are the barbell color and motion information between each frame. The experimenta...

We show on the basis of German that prosodic patterns change in the course of a traditional sentence-list elicitation. Two frequent methods are analyzed: sentence-frame and syntax-frame elicitations. While only the sentences of the sentence-frame elicitation show an increase in speaking rate, both elicitation methods cause a drastic reduction in the alignment variability of nuclear pitch-accent...