Neural network control of communications systems

Neural networks appear well suited to applications in the control of communications systems for two reasons: adaptivity and high speed. This paper describes application of neural networks to two problems, admission control and switch control, which exploit the adaptivity and speed property, respectively. The admission control problem is the selective admission of a set of calls from a number of inhomogeneous call classes, which may have widely differing characteristics as to their rate and variability of traffic, onto a network. It is usually unknown in advance which combinations of calls can be simultaneously accepted so as to ensure satisfactory performance. The approach adopted is that key network performance parameters are observed while carrying various combinations of calls, and their relationship is learned by a neural network structure. The network model chosen has the ability to interpolate or extrapolate from the past results and the ability to adapt to new and changing conditions. The switch control problem is the service policy used by a switch controller in transmitting packets. In a crossbar switch with input queueing, significant loss of throughput can occur when head-of-line service order is employed. A solution can be based on an algorithm which maximizes throughput. However since this solution is typically required in less than one microsecond, software implementation policy is infeasible. We will carry out an analysis of the benefits of such a policy, describe some existing proposed schemes for its implementation, and propose a further scheme that provides this submicrosecond optimization.     

A delta transform approach to loop gain-phase shaping design of robust digital control systems

This paper addresses the existence of loop gain-phase shaping (LGPS) solutions for the design of robust digital control systems for SISO, minimum-phase, continuous-time processes with parametric uncertainty. We develop the frequency response properties of LGPS for discrete-time systems using the Δ-transform, a transform method that applies to both continuous-time and discrete-time systems. A theorem is presented which demonstrates that for reasonable specifications there always exists a sampling period such that the robust digital control problem has a solution. Finally, we offer a procedure for estimating the maximum feasible sampling period for LGPS solutions to robust digital control problems.     

Robust crossfeed design for hovering rotorcraft

Control law design for rotorcraft fly-by-wire systems normally attempts to decouple the angular responses using fixed-gain crossfeeds. This approach can lead to poor decoupling over the frequency range of pilot inputs and increase the load on the feedback loops. In order to improve the decoupling performance, dynamic crossfeeds should be adopted. Moreover, because of the large changes that occur in the aircraft dynamics due to small changes about the nominal design condition, especially for near-hovering flight, the crossfeed design must be ‘robust’. A new low-order matching method is presented here to design robust crossfeed compensators for multi-input, multi-output (MIMO) systems. The technique minimizes cross-coupling given an anticipated set of parameter variations for the range of flight conditions of concern. Results are presented in this paper of an analysis of the pitch/roll coupling of the UH-60 Black Hawk helicopter in near-hovering flight. A robust crossfeed is designed that shows significant improvement in decoupling perfomance and robustness over the fixed-gain or single point dynamic compensators. The design method and results are presented in an easily used graphical format that lends significant physical insight to the design procedure. This plant precompensation technique is an appropriate preliminary step to the design of robust feedback control laws for rotorcraft.     

Capacitive microphone with a surface micromachined backplate usingelectroplating technology

A technology for surface micromachining of free-standing metal microstructures using metal electrodeposition on a sacrificial photoresist layer has been applied to a condenser microphone. Electroplating technology has been used to implement a suspended and perforated 15-μm-thick microstructure in copper, which serves as backplate electrode in the condenser microphone. The 1.8×1.8 mm ² large microphone diaphragm is in monocrystalline silicon and is fabricated with anisotropic etching of the substrate wafer. The realized prototypes have a measured sensitivity of 1.4 mV/Pa using a bias voltage of 28 V. The bandwidth is limited by an anti-resonance at 14 kHz which is due to the semi-rigid backplate. The resonance behavior of the backplate structure has been analyzed with finite element modeling with results in good agreement with measured data     

GUIDELINES FOR DESIGNING EIS INTERFACES Meeting Executives' Information Needs

For users of an executive information system (EIS), the EIS interface is the system and is crucial to the EIS's success. These guidelines for designing EIS interfaces are based on studies of actual EIS interfaces that meet the unique information needs of executives.     

ENHANCING THE CREATIVITY OF REENGINEERING Techniques for Making IS More Creative

Industries in the US continue to lose ground in international competition. If IS is to help change that trend, it will have to become more creative. Creativity improvement programs are being introduced in other areas of the company— now is the time for IS organizations to follow suit.     

First break refraction event picking using fuzzy logic systems

First break picking is a pattern recognition problem in seismic signal processing, one that requires much human effort and is difficult to automate. The authors' goal is to reduce the manual effort in the picking process and accurately perform the picking. Feedforward neural network first break pickers have been developed using backpropagation training algorithms applied either to an encoded version of the raw data or to derived seismic attributes which are extracted from the raw data. The authors summarize a study in which they applied a backpropagation fuzzy logic system (BPFLS) to first break picking. The authors use derived seismic attributes as features, and take lateral variations into account by using the distance to a piecewise linear guiding function as a new feature. Experimental results indicate that the BPFLS achieves about the same picking accuracy as a feedforward neural network that is also trained using a backpropagation algorithm; however, the BPFLS is trained in a much shorter time, because there is a systematic way in which the initial parameters of the BPFLS can be chosen, versus the random way in which the weights of the neural network are chosen     

Statistical synchronization among participants in real-time multimedia conferencing

In this paper, an algorithm to determine the set of packets generated continuously and periodically from different participants that are arriving at a node either for mixing at the master of a conference, or for simply playing back at a regular participant of a conference, is proposed. The essence of the algorithm is to estimate the expected packet arrival time (or reference time) for each participant. With the reference time at hand, the maximum jitter and the optimum waiting time for a mixer to wait packets from all participants can be determined. An enhancement to improve synchronization which deals with the estimation of the time offsets between the individual periods of the sources and the period of the receiver is also presented. The error of the proposed algorithm is enumerated by the Chernoff bound and demonstrated by simulation and is shown to be acceptable in practical application. The algorithm can also be employed when traffic sources operate with different periods.     

Robotica: a Mathematica package for robot analysis

Robotica is a computer aided design package for robotic manipulators developed in the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. It encapsulates over 30 functions into a Mathematica package allowing efficient symbolic and numeric calculation of kinematic and dynamic equations for multi-degree-of-freedom manipulators. An X-Windows front end that utilizes the interprocess communication features of Mathematica 2.1 has also been created for ease of use. This paper describes the most important features of the package and how they are used