Design and implementation of a field programmable CRC circuit architecture

The design and implementation of a programmable cyclic redundancy check (CRC) computation circuit architecture, suitable for deployment in network related system-on-chips (SoCs) is presented. The architecture has been designed to be field reprogrammable so that it is fully flexible in terms of the polynomial deployed and the input port width. The circuit includes an embedded configuration controller that has a low reconfiguration time and hardware cost. The circuit has been synthesised and mapped to 130-nm UMC standard cell [application-specific integrated circuit (ASIC)] technology and is capable of supporting line speeds of 5 Gb/s. © 2006 IEEE.

Embedded C programming: a practical course introducing programmable microprocessors

This paper presents a new laboratory-based module for embedded systems teaching, which addresses the current lack of consideration for the link between hardware development, software implementation, course content and student evaluation in a laboratory environment. The course introduces second year undergraduate students to the interface between hardware and software and the programming of embedded devices; in this case, the PIC (originally peripheral interface controller, later rebranded programmable intelligent computer) microcontroller. A hardware development board designed for use in the laboratories of this module is presented. Through hands on laboratory experience, students are encouraged to engage with practical problem-solving exercises and develop programming skills across a broad range of scenarios.

Using CORBA's advanced services to enhance the integrity of QoS management programmable networks

The development of wideband network services and the new network infrastructures to support them have placed much more requirements on current network management systems. Issues such as scalability, integrity and interoperability have become more important. Existing management systems are not flexible enough to support the provision of Quality of Service (QoS) in these dynamic environments. The concept of Programmable Networks has been proposed to address these requirements. Within this framework, CORBA is regarded as a middleware technology that can enable interoperation among the distributed entities founds in Programmable Networks. By using the basic CORBA environment in a heterogeneous network environment, a network manager is able to control remote Network Elements (NEs) in the same way it controls its local resources. Using this approach both the flexibility and intelligence of the overall network management can be improved. This paper proposes the use of two advanced features of CORBA to enhance the QoS management in a Programmable Network environment. The Transaction Service can be used to manage a set of tasks, whenever the management of elements in a network is correlated; and the Concurrency Service can be used to coordinate multiple accesses on the same network resources. It is also shown in this paper that proper use of CORBA can largely reduce the development and administration of network management applications.

A recursive rule base adjustment algorithm for a fuzzy logic controller

This paper introduces a recursive rule base adjustment to enhance the performance of fuzzy logic controllers. Here the fuzzy controller is constructed on the basis of a decision table (DT), relying on membership functions and fuzzy rules that incorporate heuristic knowledge and operator experience. If the controller performance is not satisfactory, it has previously been suggested that the rule base be altered by combined tuning of membership functions and controller scaling factors. The alternative approach proposed here entails alteration of the fuzzy rule base. The recursive rule base adjustment algorithm proposed in this paper has the benefit that it is computationally more efficient for the generation of a DT, and advantage for online realization. Simulation results are presented to support this thesis. (c) 2005 Elsevier B.V. All rights reserved.

Genetic algorithms for local controller network construction

Local Controller Networks (LCNs) provide nonlinear control by interpolating between a set of locally valid, subcontrollers covering the operating range of the plant. Constructing such networks typically requires knowledge of valid local models. This paper describes a new genetic learning approach to the construction of LCNs directly from the dynamic equations of the plant, or from modelling data. The advantage is that a priori knowledge about valid local models is not needed. In addition to allowing simultaneous optimisation of both the controller and validation function parameters, the approach aids transparency by ensuring that each local controller acts independently of the rest at its operating point. It thus is valuable for simultaneous design of the LCNs and identification of the operating regimes of an unknown plant. Application results from a highly nonlinear pH neutralisation process and its associated neural network representation are utilised to illustrate these issues.