Search

This paper proposes a step size control method capable of steadily canceling acoustic echo resisting double talk. The method is characterized by applying a sub-adaptive filter to the control. The step size and the number of taps of the sub- adaptive filter are larger and fewer than those of the main adaptive filter used for canceling the acoustic echo, respectively. Accordingly, the sub-adaptive filter can reduce the residual echo more rapidly than the main adaptive filter. The proposed method applies the step size calculated using the residual echo to the main adaptive filter, and thereby, quickly and steadily reduces the acoustic echo. This paper finally verifies that the proposed method can provide almost the same convergence speed as that obtained by applying a fixed large step size to the main adaptive filter.

The distribution of coronary blood volume is of fundamental importance to cardiac function. Previous investigators have demonstrated that myocardial vascular volume varies with both perfusion pressure and contraction. The purpose of this study is to measure vascular volume in an isolated rabbit heart model under a variety of controlled mechanical conditions using 3-D MCE. Isolated rabbit hearts were perfused with a room temperature crystalloid solution in a Langendorff perfusion apparatus and a small balloon was placed inside the left ventricle and attached to a volume infusion pump. Digital images of the heart were acquired with a Volumetrics 3D ultrasound scanner at perfusion pressures of 0, 30, and 50 mmHg without and with a microbubble-based contrast agent. LV pressure was held at a constant level of 0 mmHg. Regional videointensity and LV area were measured from short axis images in six hearts. Background-subtracted videointensity increased linearly with normalized coronary blood flow (R/sup 2/=.99), demonstrating the ability of this method to noninvasively determine myocardial perfusion. Coronary vascular volume was estimated using a calibration technique and assuming the perfused myocardium may be modeled as a composite material, consisting of incompressible tissue and distensible vessels. Coronary volume was estimated to be 16-24% of the myocardium, comparable to values found in previous studies. Our method may be extended to noninvasively measuring regional coronary volume in patients, thereby providing an additional tool for physicians.

This paper describes how the cause of noise in a hybrid vehicle reactor was elucidated by the development of technology to analyze the coupling between the magnetic field and vibration in the high-frequency range (5 to 10 kHz) and how reactor noise was reduced as a result. To date, magnetic field and vibration analyses, for reactors have been done but mainly within conditions at the commercial frequency range (around 60 Hz). (Hagiwara, S, 1982), (Hori, Y, 1995), (Yanari, T, 1996). This paper describes how the reactor behavior in the high-frequency range (5 to 10 kHz) was clarified by constructing a suitable model and analyzing electromagnetic fields and vibration phenomena occurring in it. Experimental results were also used for the analyses. In addition, this analytical technique was used to elucidate the cause of noise and to develop a new form of reactor to reduce noise. As a result, noise was reduced by 10 dB or more.

We propose a method to self-organize a user model for realizing a text search system. The method self-organizes a model from phoneme sequences and their texts using 6 basic rules. An inference method associated with the self-organized model searches texts corresponding to inputted phoneme sequences. Experiments using 50 voice waveforms of 10 speakers show that the self-organized model is useful to realize a text search system and is robust for noisy speech utterances.

We develop a technique for robustly positioning and guiding mobile robots in the real world, such as offices and homes, by using topological maps consisting of image sequences capturing the environment. This technique uses reference interval-free continuous dynamic programming (DP) which allows positioning by spotting, but it restricts the direction of mobile robot navigation to the same one as the map creation. We propose to use the nonmonotonic continuous DP for gesture recognition, to allow the positioning of a robot within the same framework even when it navigates backwards or stops. We also propose the use of average values of local features in each section generated by horizontally dividing the omnidirectional view as rotation-invariant features to allow global positioning of a robot regardless of its direction. In addition, we demonstrate the usefulness of this technique through evaluation experiments using mobile robots.

We propose a method to recognize human speech without the restriction that the speaker should be close to the microphone for the multiple modal interface. This method has the following features: 1) to control the microphone directivity for improvement of S/N ratio by using the speaker's position estimated by the result of gesture recognition, 2) to compose the impulse response of the transfer characteristic between speakers and microphones into reference data of the recognition system. We describe the active microphone method in detail, and show its effectivity through several experiments. Then, we discuss the results.

A spotting algorithm to recognize the meanings of human gestures from motion images is proposed. Feature vectors are extracted from temporal edge image. And input image sequences are matched with models by spotting algorithm. The spotting algorithm removes the need for temporal segmentation of gesture duration and introduces frame-wise recognition. In this paper, a new spotting method called nonmonotonic continuous DP is proposed for spotting gestures and their variations such as reverse, partial and stop motions. We showed the effectiveness of the new spotting method.

In order to obtain flexibility of recognition system of human motion behaviors, omni-directional vision sensors are used for both tracking humans and getting multiple. views of different directions that allows human to move with natural behavior in large area. First, a vision-based aspect model is proposed which realize the recognition independent of the human-direction. It contains feature vector sequences that were taken from all direction around the human. Next, the authors' appearance-based feature extraction method is demonstrated to be useful for whole body motion recognition. A new technique, spatio-temporal continuous dynamic programming, allows a human to rotate even when he is doing a motion behavior.

We have been developing a localization method for an autonomous robot without using any prior knowledge or assumptions about the environment. The method is general and robust and can be used in real world robot tasks. With a map description based on a reduced image sequence, we detect a frame sequence in the map which matches an input frame sequence, by means of reference interval-free continuous dynamic programming (RIFCDP). The method can cope with changes in the robot's speed because RIFCDP can spot arbitrary frame sequences by nonlinear matching. In this paper, we show a real-time localization system, and we illustrate the effectiveness of our method in the real world by some evaluation experiments.