60,798 research outputs found
Automating control system design via a multiobjective evolutionary algorithm
This chapter presents a performance-prioritized computer aided control system design (CACSD) methodology using a multi-objective evolutionary algorithm. The evolutionary CACSD approach unifies different control laws in both the time and frequency domains based upon performance satisfactions, without the need of aggregating different design criteria into a compromise function. It is shown that control engineers' expertise as well as settings on goal or priority for different preference on each performance requirement can be easily included and modified on-line according to the evolving trade-offs, which makes the controller design interactive, transparent and simple for real-time implementation. Advantages of the evolutionary CACSD methodology are illustrated upon a non-minimal phase plant control system, which offer a set of low-order Pareto optimal controllers satisfying all the conflicting performance requirements in the face of system constraints
Asymptotic Estimates in Information Theory with Non-Vanishing Error Probabilities
This monograph presents a unified treatment of single- and multi-user
problems in Shannon's information theory where we depart from the requirement
that the error probability decays asymptotically in the blocklength. Instead,
the error probabilities for various problems are bounded above by a
non-vanishing constant and the spotlight is shone on achievable coding rates as
functions of the growing blocklengths. This represents the study of asymptotic
estimates with non-vanishing error probabilities.
In Part I, after reviewing the fundamentals of information theory, we discuss
Strassen's seminal result for binary hypothesis testing where the type-I error
probability is non-vanishing and the rate of decay of the type-II error
probability with growing number of independent observations is characterized.
In Part II, we use this basic hypothesis testing result to develop second- and
sometimes, even third-order asymptotic expansions for point-to-point
communication. Finally in Part III, we consider network information theory
problems for which the second-order asymptotics are known. These problems
include some classes of channels with random state, the multiple-encoder
distributed lossless source coding (Slepian-Wolf) problem and special cases of
the Gaussian interference and multiple-access channels. Finally, we discuss
avenues for further research.Comment: Further comments welcom
Carrier Frequency Offset Estimation for OFDM Systems using Repetitive Patterns
This paper deals with Carrier Frequency Offset (CFO) estimation for OFDM systems using repetitive patterns in the training symbol. A theoretical comparison based on Cramer Rao Bounds (CRB) for two kinds of CFO estimation methods has been presented in this paper. Through the comparison, it is shown that the performance of CFO estimation can be improved by exploiting the repetition property and the exact training symbol rather than exploiting the repetition property only. The selection of Q (number of repetition patterns) is discussed for both situations as well. Moreover, for exploiting the repetition and the exact training symbol, a new numerical procedure for the Maximum-Likelihood (ML) estimation is designed in this paper to save computational complexity. Analysis and numerical result are also given, demonstrating the conclusions in this paper
A Formula for the Capacity of the General Gel'fand-Pinsker Channel
We consider the Gel'fand-Pinsker problem in which the channel and state are
general, i.e., possibly non-stationary, non-memoryless and non-ergodic. Using
the information spectrum method and a non-trivial modification of the piggyback
coding lemma by Wyner, we prove that the capacity can be expressed as an
optimization over the difference of a spectral inf- and a spectral sup-mutual
information rate. We consider various specializations including the case where
the channel and state are memoryless but not necessarily stationary.Comment: Accepted to the IEEE Transactions on Communication
Business and sustainability - a shared experience
One of the aims of university education is to prepare young people to be responsible citizens for the future. In the business world, the notion of sustainability is increasingly recognised as an important agenda. Both the Higher Education Funding Council (2008) and the Quality Assurance Agency (2014) acknowledge the critical role of higher education in educating socially responsible and ethically aware graduates. In line with this trend, many business schools have responded by offering sustainability related subjects and exploring pedagogical tools for engagement. Developing sustainability literacy (Stibbe 2011), shifting mindsets (Stubbs and Cocklin, 2008), developing critical thinking skills (Brookfield, 2011) and creating significant learning experiences for students (Dee Fink 2003) are just some examples of approaches which have proved successful. However, such initiatives and the concept of sustainability itself pose some difficult educational challenges for both educators and students.
This paper explores the impact of an innovative module on business and sustainability entitled Develop Sustainable Enterprises which is offered as an option to second year students in the Business School at Canterbury Christ Church University. This is the second year that the module has run and sixty five students elected to participate. Evidence of impact has been gathered (a) using a pre and post module questionnaire; (b) through the ‘voices’ of four students who have responded to the module in different ways. Tutor reflections provide an additional viewpoint. The student contributions make this an unusual and strongly grounded presentation which will illustrate a shared experience between students and tutor on a learning journey
Evolutionary L∞ identification and model reduction for robust control
An evolutionary approach for modern robust control oriented system identification and model reduction in the frequency domain is proposed. The technique provides both an optimized nominal model and a 'worst-case' additive or multiplicative uncertainty bounding function which is compatible with robust control design methodologies. In addition, the evolutionary approach is applicable to both continuous- and discrete-time systems without the need for linear parametrization or a confined problem domain for deterministic convex optimization. The proposed method is validated against a laboratory multiple-input multiple-output (MIMO) test rig and benchmark problems, which show a higher fitting accuracy and provides a tighter L�¢���� error bound than existing methods in the literature do
Second-Order Asymptotics for the Classical Capacity of Image-Additive Quantum Channels
We study non-asymptotic fundamental limits for transmitting classical
information over memoryless quantum channels, i.e. we investigate the amount of
classical information that can be transmitted when a quantum channel is used a
finite number of times and a fixed, non-vanishing average error is permissible.
We consider the classical capacity of quantum channels that are image-additive,
including all classical to quantum channels, as well as the product state
capacity of arbitrary quantum channels. In both cases we show that the
non-asymptotic fundamental limit admits a second-order approximation that
illustrates the speed at which the rate of optimal codes converges to the
Holevo capacity as the blocklength tends to infinity. The behavior is governed
by a new channel parameter, called channel dispersion, for which we provide a
geometrical interpretation.Comment: v2: main results significantly generalized and improved; v3: extended
to image-additive channels, change of title, journal versio
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