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In this paper, we address robust iterative learning control (ILC) problem for nonrepetitive systems subject to iteration-varying desired references generated by high-order internal models (HOIM). A modified high-order ILC algorithm is proposed by incorporating HOIM into the ILC algorithm design. We give one condition to guarantee the bounded system trajectories and tracking errors under the assumption...
We propose a novel approach for the crowd anomaly detection in multiple cameras with non-overlapping and visible views. As we all know that there are some kinds of information hidden in the non-overlapping fields always. In this paper, we will mine time dependence data so that we can analyze the crowd anomaly detection from time dimension's angle. Firstly, we have to preprocess the real scene using...
American death series, which shows the monthly accidental deaths in the USA between 1973 and 1978, is a multicomponent time series. We analyze this well-known series via the singular spectrum analysis (SSA) based blind source separation (BSS) technique. SSA is a powerful approach to decomposing the multicomponent time series. There is an important factor when SSA is used for extracting the principal...
The detection of nonstationarity and nonlinear dynamics of nonstationary chaotic time-series is a challenge issue, since the conventional methods are all based on the assumption that the objective time-series is stationary. In this paper, we propose a new method for analyzing the nonstationary chaotic time-series, i.e. the phase space reconstruction is directly done on the nonstationary time-series...
In this paper, a novel global abnormal event detection algorithm is proposed for multiple disjoint synchronous camera network. We treat detecting unusual global events as discovering context-incoherent patterns through learning temporal dependencies between distributed local activities observed within and across camera views. Trajectories are firstly extracted using mean-shift approach in each camera...
We propose a novel approach for the crowd anomaly detection in multiple cameras with non-overlapping view. In this paper, we refer to the activities of crowd in far-field scenes. Firstly, we present a model for learning all of the motion patterns under single camera view, which are regarded as the normal situation. In the surveillance region, we mark the entrances and exits under the single camera...
Nowadays gesture recognition is a hot topic in the field of human-computer interaction (HCI). HCI develop very fast, and also brings surprise to us constantly. In this paper, we propose a novel approach based on improved HMMs with entropy to recognize the 3D gesture. In our method, there are two steps to recognize a gesture: 1. detect the key nodes of body with extracting the skeleton point. A low-pass...
In this paper we present a method to detect and localize abnormal events in crowded scene. Most existing methods use the patch of optical flow or human tracking based trajectory as representation for crowd motion, which inevitably suffer from noises. Instead, we propose the employment of a new and efficient feature, short-term trajectory, which represent the motion of the visible and constant part...
A model predictive controller based on iterative learning control is proposed. This algorithm which combines real-time control with iterative learning control is developed to address the trajectory tracking for a class of repetitive system with non-repetitive disturbances. First, a generic model which describes the state transition of a time-varying linear repetitive system along batch indices as...
Recent developments to the electron optics simulator (EOS), an electron gun and collector design tool, are reported in this present. The code has been formally released at 2007, and there are some modifications and new methods to improve the code up to now.
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