Clouds have double functions for lidar: noise and useful information. In this study, the clouds were separated from temporal-spatial coherent Doppler wind lidar (CDWL) with a high temporal resolution image based on morphological open filter, which produced filtered cloud image. First, The wavelet covariance transform was employed to retrieve planetary boundary layer height (PBLH) including surf...

A Kalman-filter method for power control is proposed for broadband, packet-switched TDMA wireless networks. By exploiting the temporal correlation of co-channel interference, a Kalman filter is used to predict future interference power. Based on the predicted interference and estimated path gain between the transmitter and receiver, transmission power is determined to achieve a desired signal-t...

A Kalman-filter method for power control is proposed for broadband, packet-switched TDMA wireless networks. By exploiting the temporal correlation of co-channel interference, a Kalman filter is used to predict future interference power. Based on the predicted interference and estimated path gain between the transmitter and receiver, transmission power is determined to achieve a desired signal-t...

Original video signals are often corrupted by a certain amount of noise originating from the camera electronics. As a result of the gamma correction in cameras, the observed noise is signal dependent. We present a spatio-temporal order-statistic (OS) noise filter that takes into account the gamma correction in the camera. The calculation of the filter coefficients requires higher-order order-st...

In the problem of speech enhancement, where a speech signal is corrupted by.In this paper, we propose to combine the Kalman filter with a recent speech enhancement technique, called the phase spectrum compensation procedure, or.we present a class of Kalman filter-based algorithms with some extensions, modifications. These algorithms with alternative speech enhancement algorithms. Conversations ...

Discriminative correlation filter (DCF) based tracking algorithms have obtained prominent speed and accuracy strengths, which attracted extensive attention research. However, some unavoidable deficiencies still exist. For example, the circulant shifted sampling process is likely to cause repeated periodic assumptions boundary effects, degrades tracker’s discriminative performance, target not ea...

We present an approach to localized object detection that is not dependent upon background image construction or object modeling. It is designed to work through camera embedded software using spare processing capacity in a visual signal processor. It uses a localized temporal difference change detector and a particle filter type likelihood to detect possible trackable objects, and to find a poi...

Memory is a central component of our cognitive lives, and it is accomplished by multiple neurobiological memory systems that encode, retain, and retrieve different forms of information about past experience. Memory for the past can be used to build predictive models in the present and thus can guide current thoughts, decisions, and actions. For example, memory enables us to discriminate novel p...

We propose a simultaneous spatiotemporal filter optimization algorithm for the single trial ElectroEncephaloGraphy (EEG) classification problem. The algorithm is a generalization of the Common Spatial Pattern (CSP) algorithm, which incorporates non-homogeneous weighting of the crossspectrum matrices. The spectral weighting coefficients and the spatial filter are alternately updated. The validat...

In this paper we present a filter for identifying posts from eyewitnesses to various event types on Twitter, including shootings, police activity, and protests. The filter combines sociolinguistic markers and targeted language content with straightforward keywords and regular expressions to yield good accuracy in the returned tweets. Once a set of eyewitness posts in a given semantic context ha...