31744215
Multiband room effect simulator for 5.1-channel sound system
The paper investigates a new room effect simulator with different quality of audio sound sources for a 5.1-channel sound system. The audio effect relates its impulse response with different room dimensions. A multiband equalizer is designed to generate many kinds of music impressions. We also modify the mono Dolby surround decoder into a simplified surround decoder so that the stereo room simulator can generate 5.1-channel surround outputs. All experiments are at a sampling rate of 44.1 kHz and 16 bits per sample. By the room effect simulator, we can get a full and a live listening experience.
5592923
Temperature control with a neural fuzzy inference network
Although multilayered backpropagation neural networks (BPNNs) have demonstrated high potential in adaptive control, their long training time usually discourages their applications in industry. Moreover, when they are trained online to adapt to plant variations, the over-tuned phenomenon usually occurs. To overcome the weakness of the BPNN, we propose a neural fuzzy inference network (NFIN) suitable for adaptive control of practical plant systems in general and for adaptive temperature control of a water bath system in particular. The NFIN is inherently a modified Takagi-Sugeno-Kang (TSK)-type fuzzy rule based model possessing a neural network's learning ability. In contrast to the general adaptive neural fuzzy networks, where the rules should be decided in advance before parameter learning is performed, there are no rules initially in the NFIN. The rules in the NFIN are created and adapted as online learning proceeds via simultaneous structure and parameter identification. The NFIN has been applied to a practical water bath temperature control system. As compared to the BPNN under the same training procedure, the simulated results show that not only can the NFIN greatly reduce the training time and avoid the over-tuned phenomenon, but the NFIN also has perfect regulation ability. The performance of the NFIN is compared to that of the traditional PID controller and fuzzy logic controller (FLC) on the water bath temperature control system. The three control schemes are compared, with respect to set point regulation, ramp-point tracking, and the influence of unknown impulse noise and large parameter variation in the temperature control system. The proposed NFIN scheme has the best control performance.
15301928
New techniques on deformed image motion estimation and compensation
In this paper, new techniques for deformed image motion estimation and compensation using variable-size block-matching are proposed, which can be applied to an image sequence compression system or a moving object recognition system. The motion estimation and compensation techniques have been successfully applied in the area of image sequence coding. Many research papers on improving the performance of these techniques have been published; many directions are proposed, which can all lead to better performance than the conventional techniques. Among them, both generalized block-matching and variable-size block-matching are successfully applied in reducing the data rate of compensation error and motion information, respectively. These two algorithms have their merits, but suffer from their drawbacks. Moreover, reducing the data rate in compensation error is sometimes increasing the data rate in motion information, or vice versa. Based on these two algorithms, we propose and examine several algorithms which are effective in reducing the data rate. We then incorporate these algorithms into a system, in which they work together to overcome the disadvantages to individual and keep their merits at the same time. The proposed system can optimally balance the amount of data rate in two aspects (i.e., compensation error and motion information). Experimental results show that the proposed system outweighs the conventional techniques. Since we propose a recovery operation which tries to recover the incorrect motion vectors from the global motion, this proposed system can also be applied to the moving object recognition in image sequences.
20361854
Protein Metal Binding Residue Prediction Based on Neural Networks
Over one-third of protein structures contain metal ions, which are the necessary elements in life systems. Traditionally, structural biologists were used to investigate properties of metalloproteins (proteins which bind with metal ions) by physical means and interpreting the function formation and reaction mechanism of enzyme by their structures and observations from experiments in vitro. Most of proteins have primary structures (amino acid sequence information) only; however, the 3-dimension structures are not always available. In this paper, a direct analysis method is proposed to predict the protein metal-binding amino acid residues from its sequence information only by neural networks with sliding window-based feature extraction and biological feature encoding techniques. In four major bulk elements (Calcium, Potassium, Magnesium, and Sodium), the metal-binding residues are identified by the proposed method with higher than 90% sensitivity and very good accuracy under 5-fold cross validation. With such promising results, it can be extended and used as a powerful methodology for metal-binding characterization from rapidly increasing protein sequences in the future.
44754516
Noisy Speech Segmentation/Enhancement with Multiband Analysis and Neural Fuzzy Networks
This paper addresses the problem of speech segmentation and enhancement in the presence of noise. We first propose a new word boundary detection algorithm by using a neural fuzzy network (called ATF-based SONFIN algorithm) for identifying islands of word signals in fixed noise-level environment. We further propose a new RTF-based RSONFIN algorithm where the background noise level varies during the procedure of recording. The adaptive time-frequency (ATF) and refined time-frequency (RTF) parameters extend the TF parameter from single band to multiband spectrum analysis, and help to make the distinction of speech and noise signals clear. The ATF and RTF parameters can extract useful frequency information by adaptively choosing proper bands of the mel-scale frequency bank. Due to the self-learning ability of SONFIN and RSONFIN, the proposed algorithms avoid the need of empirically determining thresholds and ambiguous rules. The RTF-based RSONFIN algorithm can also find the variation of the background noise level and detect correct word boundaries in the condition of variable background noise level by processing the temporal relations. Our experimental results show that both in the fixed and variable noise-level environment, the algorithms that we proposed achieved higher recognition rate than several commonly used word boundary detection algorithms and reduced the recognition error rate due to endpoint detection.
4468971
Tracking a maneuvering target using neural fuzzy network
A fast target maneuver detection and highly accurate tracking technique using a neural fuzzy network based on a Kalman filter is proposed in this paper. In the automatic target tracking system, there exists an important and difficult problem: how to detect the target maneuvers and fast response to avoid miss-tracking? The traditional maneuver detection algorithms, such as variable dimension filter (VDF) and input estimation (IE) etc., are computation intensive and difficult to implement in real time. To solve this problem, neural network algorithms have been issued recently. However, normal neural networks such as backpropagation networks usually produce the extra problems of low convergence speed and/or large network size. Furthermore, the way to decide the network structure is heuristic. To overcome these defects and to make use of neural learning ability, a developed standard Kalman filter with a self-constructing neural fuzzy inference network (KF-SONFIN) algorithm for target tracking is presented in this paper. By generating possible target trajectories including maneuver information to train the SONFIN, the trained SONFIN can detect when the maneuver occurred, the magnitude of maneuver values and when the maneuver disappeared. Without having to change the structure of the Kalman filter or modeling the maneuvering target, this new algorithm, SONFIN, can always find an economic network size with a fast learning process. Simulation results show that KF-SONFIN is superior to traditional IE and VDF methods in estimation accuracy.
52872372
Modeling and Performance Analysis of a Multiserver Multiqueue System on the Grid
Grid computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and high-performance orientation. A Grid integrates and coordinates resources and users that live within different control domains with the goal of delivering nontrivial quality of service (QoS). Consequently, task management and scheduling is of central importance for the Grid-based systems. In this paper, we model the task dispatching and selecting on the distributed Grid computing system by a multiserver multiqueue (MSMQ) model, and propose a modeling and analysis technique based on Stochastic Petri Net (SPN) methods. An approximate analysis technique is also proposed to reduce the complexity of the model.
5012485
Stochastic High-Level Petri Nets and Applications
A class of stochastic Petri nets called stochastic high-level Petri nets (SHLPNs) is proposed. SHLPNs are high-level Petri nets augmented with exponentially distributed firing times. SHLPNs generally lead to models with a smaller state space. A computer marking concept is introduced that allows a considerable reduction of the number of states and induces a correct grouping of states in the Markov-domain SHLPN models of multiprocessor systems. The main advantage of modeling homogeneous systems using SHLPNs is that the resulting models are simpler and more intuitive and have a smaller number of states, as shown by examples. >
32785610
Customizing Software Libraries for Performance Portability
40804846
Question Answering in Webclopedia
SHAPE ADJECTIVE COLOR DISEASE TEXT NARRATIVE* GENERAL-INFO DEFINITION USE EXPRESSION-ORIGIN HISTORY WHY-FAMOUS BIO ANTECEDENT INFLUENCE CONSEQUENT CAUSE-EFFECT METHOD-MEANS CIRCUMSTANCE-MEANS REASON EVALUATION PRO-CON CONTRAST RATING COUNSEL-ADVICE To create the QA Typology, we analyzed 17,384 questions and their answers (downloaded from answers.com); see (Gerber, 2001). The Typology contains 94 nodes, of which 47 are leaf nodes; a section of it appears in Figure 2. Each Typology node has been annotated with examples and typical patterns of expression of both Question and Answer, as indicated in Figure 3 for Proper-Person. Question examples Question templates Who was Johnny Mathis' high school track coach? who be 's Who was Lincoln's Secretary of State? Who was President of Turkmenistan in 1994? who be of Who is the composer of Eugene Onegin? Who is the CEO of General Electric? Actual answers Answer templates Lou Vasquez, track coach of...and Johnny Mathis , of Signed Saparmurad Turkmenbachy [Niyazov], of president of Turkmenistan ...Turkmenistan’s President Saparmurad Niyazov... ’s ...in Tchaikovsky's Eugene Onegin... 's Mr. Jack Welch, GE chairman... ... ...Chairman John Welch said ...GE's | of related role-verb Figure 3. Portion of QA Typology node annotations for Proper-Person.
15260570
Dynamic priority handoff scheme in differentiated QoS wireless multimedia networks
Handoff is one of the key elements in ensuring quality of service (QoS) in mobile wireless networks. Handoff connections generally have higher priority than new connections. Traditional reservation policies that reserve some channels for handoff connections are not adaptive to traffic load changes. This paper proposes a new dynamic guard channel scheme (DGCS), which 1) adapts to various traffic loads; 2) combines differentiated QoS service model and priority handoff mechanism; 3) provides fairness for differentiated QoS services; 4) does not need to exchange state information among different cells, so it is easy to be implemented and is simple enough to be used in real time environments; 5) and utilizes network resources efficiently and puts a bound on each service blocking probability. The simulation results show that the ratios among different QoS service probabilities are guaranteed to be predefined values and system utilization is improved greatly.