Abstract: The hardware and software of the voting system of an election are described. The hardware consists of a number of computers: desktops or notebooks. The software consists of a number of programs running on these computers to produce a number of spreadsheet files of which election results can be displayed and verified. These spreadsheet files are protected with a password to prevent alterations. A voter also needs passwords for the authenticity of the vote. The vote is then entered into computer memory cells, the spreadsheet files and printed out on a piece of paper for the ballot box. This triple action will make the alteration of the election result difficult and enhance the honesty of the election.

Abstract: A new method to adjust the parameters of an adaptive Infinite Impulse Response (IIR) filter is suggested. The method adjusts the set of parameters of the pole polynomial of the filter. The parameters of the zero polynomial are calculated from the parameters of the pole polynomial. For efficiency, the pole polynomial is factored into a product of polynomials with at most quadratic order. To guarantee that the global minimum is achieved all the time, the algorithm ascertains that the new set of pole parameters gives smaller variance of the error than the set of pole parameters of the last adaptation time and the algorithm starts with the set of parameters that gives the global minimum.

Abstract: A rational function for the transfer function model of a multivariable discrete control system is suggested and its controllers are obtained. There are two types of control systems depending on the nature of the disturbance. For tracking control systems, the disturbance is a set of set point changes. For regulating control systems, the disturbance is a vector ARIMA time series. The quadratic performance controllers for these systems are similar but opposite in nature. For tracking control systems, a two and a half degrees of freedom controller can be designed for an enhanced quadratic performance. This controller uses the future values of the disturbance which are the set points of the control system for further reduction of the error. The controller is particularly useful for nonminimum phase tracking control systems.

Abstract: Two linear quadratic tracking controllers and a minimal prototype controller are presented for the control of a discrete single input and single output (SISO) tracking control system. The minimal prototype controller is an unconstrained controller. Depending on the models of the set point and the plant transfer function, this controller might be desirable. But usually one would choose one of the two linear quadratic controllers which minimize the sum of squared errors between the output and the set point variables with a penalty on that of the input variable. The one degree of freedom (1-DOF) controller performs well, but for nonminimum phase systems the two and a half degrees of freedom (2.5-DOF) controller is the stronger one as it can suppress the inverse response of a non-minimum phase system. The 1-DOF controller gives the stochastic regulating controller counterpart known as the linear quadratic Gaussian controller. A digital control chip for implementation of the controllers is also disclosed.