Binary Hopfield networks are shown to be effective in estimation of Gaussian random vectors based on partial observation. Estimation with maximum likelihood is replaced by minimization of a quadratic cost. The energy-decreasing property of Hopfield networks is applied to the minimization by making the network energy equivalent to the quadratic cost. It is proved that existence of the local minima of the network energy leads to no practical problem provided the network contains sufficiently abundant units. The resultant network is composed of subnetworks with mutually equal number of units. The activity ratio of each subnetwork represents a component of a given random vector. If some of the subnetworks are cramped in accordance with observed data, the rest of the subnetworks reconstruct the most probable values of the unobserved components of the random vector. A simulation result suggests that the network behavior is insensitive to partial damage in the connections between the units of the network.
Because the conventional ultrasonic B-mode imaging device is scanning a measured plane by a pencil beam pulse, a multi-directional information can not be detected at the same time. This paper presents an instantaneous measurement technique which is able to image the echo-tomogram by transmitting an ultrasonic fan beam pulse and processing the echo signal backscattered from the object. We measured the cross section image of the copper wires, the vinyl seet and the sponge cube in the water vessel, and discussed on the method to alter for the better by the computer simulation. The results show that spot objects can be detected perfectly and that the probe with lengthening aperture and high frequency is effective to image a plane object and a volumic object better.
In cooperative manipulation with multiple robot arms or multifingered robot hand handling a single object, simultaneous control of the object motion and of the internal force exerted by arms or fingers on the object are required. Furthermore, in case where the motion of the object is constrained in some directions due to a contact with its environment, control of the constraint force also becomes necessary. In this paper, for controlling motion of an object under constraint as well as constraint force and internal force, a cooperative dynamic hybrid control method for multiple robotic mechanisms is proposed. This method takes the manipulator dynamics and object dynamics into consideration. An experimental result is presented which shows the validity of the proposed approach.