Search results for "Algorithm"
showing 10 items of 4887 documents
Performance analysis of wideband sum-of-cisoids-based channel simulators with respect to the bit error probability of DPSK OFDM Systems
2009
In this paper, we analyze the performance of a wideband sum-of-cisoids (SOC) channel simulator w.r.t. the bit error probability (BEP) of differential phase-shift keying (DPSK) orthogonal frequency division multiplexing (OFDM) systems. Analytical BEP expressions are derived for coherent and non- coherent DPSK OFDM simulation systems in the presence of a wideband SOC channel simulator. We also study the degradations of the BEP introduced by an imperfect channel simulator. Using the deviation of the BEP as an appropriate measure, we evaluate the performance of three parameter computation methods, known as the method of exact Doppler spread (MEDS), the randomized MEDS (R-MEDS), and the Monte Ca…
A novel identification method for generalized T-S fuzzy systems
2012
Published version of an article from the journal: Mathematical Problems in Engineering. Also available from the publisher:http://dx.doi.org/10.1155/2012/893807 In order to approximate any nonlinear system, not just affine nonlinear systems, generalized T-S fuzzy systems, where the control variables and the state variables, are all premise variables are introduced in the paper. Firstly, fuzzy spaces and rules were determined by using ant colony algorithm. Secondly, the state-space model parameters are identified by using genetic algorithm. The simulation results show the effectiveness of the proposed algorithm
An Algorithm for Discretization of Real Value Attributes Based on Interval Similarity
2013
Discretization algorithm for real value attributes is of very important uses in many areas such as intelligence and machine learning. The algorithms related to Chi2 algorithm (includes modified Chi2 algorithm and extended Chi2 algorithm) are famous discretization algorithm exploiting the technique of probability and statistics. In this paper the algorithms are analyzed, and their drawback is pointed. Based on the analysis a new modified algorithm based on interval similarity is proposed. The new algorithm defines an interval similarity function which is regarded as a new merging standard in the process of discretization. At the same time, two important parameters (condition parameterαand ti…
Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes
2010
Accepted version of an article published in the journal: Pattern Recognition. Published version on Sciverse: http://dx.doi.org/10.1016/j.patcog.2010.01.018 Linear dimensionality reduction (LDR) techniques have been increasingly important in pattern recognition (PR) due to the fact that they permit a relatively simple mapping of the problem onto a lower-dimensional subspace, leading to simple and computationally efficient classification strategies. Although the field has been well developed for the two-class problem, the corresponding issues encountered when dealing with multiple classes are far from trivial. In this paper, we argue that, as opposed to the traditional LDR multi-class schemes…
On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes
2010
Published version of an article from the Book: AI 2010: Advances in Artificial Intelligence, Spinger. Also available on Springerlink: http://dx.doi.org/10.1007/978-3-642-17432-2_16 This paper concerns the use of Prototype Reduction Schemes (PRS) to optimize the computations involved in typical k-Nearest Neighbor (k-NN) rules. These rules have been successfully used for decades in statistical Pattern Recognition (PR) applications, and have numerous applications because of their known error bounds. For a given data point of unknown identity, the k-NN possesses the phenomenon that it combines the information about the samples from a priori target classes (values) of selected neighbors to, for …
A two-armed bandit collective for examplar based mining of frequent itemsets with applications to intrusion detection
2011
Chapter from the book: Computational Collective Intelligence. Technologies and Applications. Also available from the publisher at SpringerLink: http://dx.doi.org/10.1007/978-3-642-23935-9_7 Over the last decades, frequent itemset mining has become a major area of research, with applications including indexing and similarity search, as well as mining of data streams, web, and software bugs. Although several efficient techniques for generating frequent itemsets with a minimum support (frequency) have been proposed, the number of itemsets produced is in many cases too large for effective usage in real-life applications. Indeed, the problem of deriving frequent itemsets that are both compact an…
Forward Kinematic Modelling with Radial Basis Function Neural Network Tuned with a Novel Meta-Heuristic Algorithm for Robotic Manipulators
2022
The complexity of forward kinematic modelling increases with the increase in the degrees of freedom for a manipulator. To reduce the computational weight and time lag for desired output transformation, this paper proposes a forward kinematic model mapped with the help of the Radial Basis Function Neural Network (RBFNN) architecture tuned by a novel meta-heuristic algorithm, namely, the Cooperative Search Optimisation Algorithm (CSOA). The architecture presented is able to automatically learn the kinematic properties of the manipulator. Learning is accomplished iteratively based only on the observation of the input–output relationship. Related simulations are carried out on a 3-Degrees…
Anomaly Detection in Traffic Surveillance Videos Using Deep Learning
2022
In the recent past, a huge number of cameras have been placed in a variety of public and private areas for the purposes of surveillance, the monitoring of abnormal human actions, and traffic surveillance. The detection and recognition of abnormal activity in a real-world environment is a big challenge, as there can be many types of alarming and abnormal activities, such as theft, violence, and accidents. This research deals with accidents in traffic videos. In the modern world, video traffic surveillance cameras (VTSS) are used for traffic surveillance and monitoring. As the population is increasing drastically, the likelihood of accidents is also increasing. The VTSS is used to detect abno…
Review Paper: Are reproductive skew models evolutionarily stable?
2003
Reproductive skew theory has become a popular way to phrase problems and test hypotheses of social evolution. The diversity of reproductive skew models probably stems from the ease of generating new variations. However, I show that the logical basis of skew models, that is, the way in which group formation is modelled, makes use of hidden assumptions that may be problematical as they are unlikely to be fulfilled in all social systems. I illustrate these problems by re-analysing the basic concessive skew model with staying incentives. First, the model assumes that dispersal is an all-or-nothing response: all subordinates disperse as soon as concessions drop below a certain value. This leads …
Study of the column efficiency using gradient elution based on Van Deemter plots.
2018
Performance of chromatographic columns is of major importance in the development of more efficient separation methods. So far, a common practice is to study the column behavior in isocratic elution by modifying the flow rate and fitting the theoretical plate height values versus the mobile phase linear velocity, according to the Van Deemter equation. In this work, an approach is presented to extend the measurement of efficiency to linear gradient elution, where the mean retention factor is kept constant at each assayed flow. This avoids a possible source of uncertainty due to the change in the distribution equilibria profile, and makes the mean interactions with the stationary phase in grad…