We previously introduced a new Bayesian predictive classification (BPC) approach to robust speech recognition and showed that the BPC is capable of coping with many types of distortions. We also learned that the effic...
详细信息
In this paper,a novel object-oriented hierarchical video segmentation and representation algorithm is proposed based on four-component video model,where the local variance contrast and the frame difference contrast ar...
详细信息
In this paper,a novel object-oriented hierarchical video segmentation and representation algorithm is proposed based on four-component video model,where the local variance contrast and the frame difference contrast are selected for generating the 2D spatiotemporal entropy. The extracted object is first represented by a group of(4 x 4) blocks coarsely,then the intra-block edge extraction on edge blocks and the joint spatiotemporal similarity test among neighboring blocks are further performed for determining the meaningful real objects. This proposed hierarchical segmentation algorithm may be very useful for MPEG-4 applications.A novel fast algorithm is also introduced for reducing the search burden. Moreover,this unsupervised algorithm also makes the automatic image and video segmentation possible.
This paper reports on a workshop on Problem Formulation in Multi-Criteria Decision Analysis held at SPUDM97. The focus of the workshop was the problem formulation phase which occurs between the analyst meeting a perso...
详细信息
作者：
Adrian G. AlfordfChris J. HarristAdvanced Engineering Department
GKN Westland Helicopters Ltd Yeovil Somerset BA20 2YB UK. Image
Speech and Intelligent Systems (ISIS) Research Group Department of Electronics and Computer Science University of Southampton Southampton SO 171 BJ UK
The process of calculating optimal actuator demands for MIMO dynamic systems which feature position/rate limited actuators is investigated. Order 3 B-splines are identified as a good method for parsimoniously represen...
详细信息
The process of calculating optimal actuator demands for MIMO dynamic systems which feature position/rate limited actuators is investigated. Order 3 B-splines are identified as a good method for parsimoniously representing actuator demands. A least squares optimization algorithm is used to calculate the B-spline parameters necessary to match the plant and reference models’ responses. The reference model is assumed to contain output and output rate constraints which are to be respected by the plant model. This technique is successfully applied to a nonlinear helicopter model and is able to respect the reference model’s angular velocity (output) and angular acceleration (output rate) constraints at all times.
By combining properties of fuzzy systems and neural networks, neurofuzzy modelling is ideally suited to many system identification and data modelling applications. Recently, data-driven model construction algorithms h...
详细信息
By combining properties of fuzzy systems and neural networks, neurofuzzy modelling is ideally suited to many system identification and data modelling applications. Recently, data-driven model construction algorithms have been developed to identify these models. These algorithms have proved essential for producing accurate parsimonious models. However, due to problems with sparse data and restricted model structures, models with high model variance are often produced. Thus resulting in models which generalise poorly. In this paper local Bayesian inference techniques are applied to neurofuzzy models, multiple prior probability density functions are placed on the weights and superfluous model variance is controlled. This gives a form of regularisation where Bayesian estimation produces simple re-estimation formulae which identify a suitable bias/variance balance from the data. This approach is considered a post-processing step to model construction, the merits of which are demonstrated by the application to a real world data set.
In this paper, novel methods for performing condition monitoring for power station turbine shafts are presented. The objective of this work is to investigate methods for producing accurate turbine vibration fault alar...
详细信息
In this paper, novel methods for performing condition monitoring for power station turbine shafts are presented. The objective of this work is to investigate methods for producing accurate turbine vibration fault alarms during turbine shaft rundowns. Wavelet packet analysis is employed to extract spectral features from healthy vibration signals and the probability density functions of these features are estimated. Both Gaussian models, using Bayesian inferencing, and mixture models are employed. Preliminary results show that the more computationally expensive mixture models produce more accurate density estimates and hence more reliable fault alarms.
One of the major difficulties in controlling software development project cost overruns and schedule delays has been developing practical and accurate software cost models. Software development could be modeled as an ...
详细信息
One of the major difficulties in controlling software development project cost overruns and schedule delays has been developing practical and accurate software cost models. Software development could be modeled as an economic production process and we therefore propose a theoretical approach to software cost modeling. Specifically, we present the Minimum Software Cost Model (MSCM), derived from economic production theory and systems optimization. The MSCM model is compared with other widely used software cost models, such as COCOMO and SLIM, on the basis of goodness of fit and quality of estimation using software project data sets available in the literature. Judged by both criteria, the MSCM model is comparable to, if not better than, the SLIM, and significantly better than the rest of the models. In addition, the MSCM model provides some insights about the behavior of software development processes and environment, which could be used to formulate guidelines for better software project management polic es and practices.
暂无评论