In this paper, two basic methods of signal processings to make the systematic diagnosis of subtle heart malfunctions possible are proposed, by utilizing the time-frequency information of heart sounds and noises detected only on the chest surface. That is, a simple method of determining the average time length for nonstationary power spectral analysis, based on the evaluation of the local 1 st and 2 nd order cumulant variation of the observed data, along with the heart dynamics, and an advanced method of discriminant analysis, that can extract the time-frequency characteristic parameters, properly fitted to the analysed heart sounds and noises, by the additional use of multiple regression analysis. The principles of these methods and their fundamental features as well as the effectiveness of sophisticated processings for computer-aided automatic diagnosis of heart malfunctions are shown, along with fundamental results of experiments.
The position and the speed control systems used in the industrial robots or the autonomous vehicles have to be developed for the load torque changing with time. However, it is difficult to set the load touque as a function of time by use of passive load, suth as the friction and the inertia mass. This paper describes the principle and the performance of a load torque simulator which is constructed by a dc generator and a current type dc amplifier and controlled by a micropocessor. The simulator is able to produce some kinds of torque such as inertia viscous and elastic load torque which has arbitrary magnitude and is set as a function of time. The responses of the dc motor coupled to the simulator are measured to verify the availability of this simulator. Furthermore, the responses calculated theoretically are also shown.
Precise attitude and shape control of flexible spacecraft requires active control of flexural vibrations. This paper first derives a general closed loop characteristic equation of a flexural vibration control system equipped with arbitrary numbers of non-point actuators and sensors whose regions of actions and observations are expressed by weight functions. Then, the characteristic equation in a determinantal form is expanded in a mathematically tractable form in which each coefficient is a product of an actuator-dependent determinant, a sensor-dependent determinant and a compensator-dependent determinant. By applying the perturbation technique to the expanded characteristic equation, it is shown that a modal stabilizing condition can be obtained for a rate and position feedback control system. Finally, a numerical example is given to illustrate the usage of the condition.
Inverse problems are often encountered in various fields of engineering. A method is proposed in this paper to obtain a solution for the Fredholm integral equations of the first kind, which define a typical case of inverse problems. The method uses a neural network which is able to learn the inverse mapping from the output. function to input function of the integral equation under some a priori information on relevant problems. The network which has terminated its learning successfully can be expected to give a reasonable solution for not-learned input data from its association functions. It was shown for the cases of Phillips' example and of the size distribution measurement of aerosol particles by multi-wavelength laser radar that the method yields rather more stable solutions as compared with those by the conventional regularization method.