The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
CPU-FPGA heterogeneous platforms offer a promising solution for high-performance and energy-efficient computing systems by providing specialized accelerators with post-silicon reconfigurability. To unleash the power of FPGA, however, the programmability gap has to be filled so that applications specified in high-level programming languages can be efficiently mapped and scheduled on FPGA. The above...
Cuff-less blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for long-term BP monitoring. However, state-of-art PTT models are unable to trace the change of pressure baseline in subjects, which limits their application in long-term BP tracking. This study investigated the relationship between the change of pressure baseline and pulse waveform in long-term BP monitoring...
Sub-harmonic oscillation is a key factor causing instability for current-mode controlled single-inductor dual-output (SIDO) Buck converter. To inhibit the sub-harmonic oscillation of the converter and to extend its stable operating range, the ramp compensation technique is introduced in this paper. The discrete iterative map model of current-mode controlled SIDO Buck converter with ramp compensation...
The RPCA model has achieved good performances in various applications. However, two defects limit its effectiveness. Firstly, it is designed for dealing with data in matrix form, which fails to exploit the structure information of higher order tensor data in some pratical situations. Secondly, it adopts L1-norm to tackle noise part which makes it only valid for sparse noise. In this paper, we propose...
Time-based flow management provides arrival aircraft schedules based on arrival airport conditions, airport capacity, required spacing, and weather conditions. In order to meet a scheduled time at which aircraft can cross an airport arrival meter fix prior to entering the airport terminal airspace, air traffic controllers impose regulations on air traffic. Severe weather may create an airport arrival...
Rain streaks removal is an important issue of the outdoor vision system and has been recently investigated extensively. In this paper, we propose a novel tensor based video rain streaks removal approach by fully considering the discriminatively intrinsic characteristics of rain streaks and clean videos, which needs neither rain detection nor time-consuming dictionary learning stage. In specific, on...
This research introduces a low-power, light-weight wearable powered waist exoskeleton with mechanical clutch. By processing the signals from multiple sensors, the human movement intention can be precisely identified and estimated. The exoskeleton can help reduce the work done by human muscle and has a loading capacity up to 20kg. Through the mechanical clutches applied, the exoskeleton can lock the...
Convolutional neural network (CNN) is more and more important in pattern recognition. In this work, we adopt label relations and long short-term memory (LSTM) to develop an accurate CNN-based scene classification algorithm. Traditional scene classification algorithms assume that labels are mutually exclusive. However, this is not reasonable when an image has a variety of objects and hence has multiple...
In this paper, we propose a novel object based graph framework for video representation. The proposed framework describes a video as a graph, in which objects are represented by nodes, and their relations between objects are represented by edges. We investigated several spatial and temporal features as the graph node attributes, and different features of spatial-temporal relationship between objects...
This paper proposes a novel deep convolutional neural network (CNN), called sparse coding convolutional neural network (SC-CNN), to address the problem of sound event recognition and retrieval task. Unlike the general framework of a CNN, in which feature learning process is performed hierarchically, the proposed framework models the whole memorizing procedures in the human brain, including encoding,...
Ternary Content Addressable Memory (TCAM) capacity problem is an important issue in Software-Defined Networking. Rule caching is an efficient technique to solve the TCAM capacity problem. However, there exists rule dependency problem in wildcard-rule caching technique. In this paper, we utilize cover-set method to solve the rule dependency problem and propose a wildcard-rule caching algorithm to cache...
The convolutional neural network (CNN) is more and more popular in computer vision and widely used in acoustic signal processing, image classification, and image segmentation. In this work, an architecture which is a combination of the 3-D convolutional neural network and the long short term memory (LSTM) was proposed for action recognition. It stacks the consecutive video frames, extracts spatial...
Transmit diversity code filters set (TDCFSs) adopted in ATSC3.0 is a method using all-pass linear filters to minimize the possibility of cross-interference among the transmitted signals. This paper presents a new cyclic algorithm for the filter set design in TDCFS. In the case of designing the filter set to have almost identical correlation property, the proposed algorithm requires less iteration...
360 degree video compression and delivery is one of the key components of virtual reality (VR) applications. In such applications, the users may freely control and navigate the captured 3D environment from any viewing direction. Given that only a small portion of the entire video is watched at any time, fetching the entire 360 degree raw video is therefore unnecessary and bandwidth-consuming. In this...
Palmprint recognition has drawn a lot of attentions during recent years. Different features and algorithms have been proposed for palmprint recognition in the past such as Gabor-based features, wavelet features, and histogram of oriented lines. In this paper, a powerful image representation, so called deep scattering network, is used for recognition. Scattering network is a convolutional network where...
A low-voltage high-swing voltage-biased Colpitts voltage-controlled oscillator (VCO) is proposed for wireless applications. A small capacitive voltage divide factor is chosen to enhance the output swing and improve the phase noise performance. To further enhance the negative resistance, and thus decrease the start-up time, the bulk terminals of the gm-boosting transistors are dynamic-biased by the...
Subspace learning is an important problem, which has many applications in image and video processing. It can be used to find a low-dimensional representation of signals and images. But in many applications, the desired signal is heavily distorted by outliers and noise, which negatively affect the learned subspace. In this work, we present a novel algorithm for learning a subspace for signal representation,...
In this work, we focus on the problem of city security based on the massive amount of crime statistics data. Combined with city crime statistics data, fuzzy comprehensive evaluation method is used to judge the safety grade of the city, and the weight of the evaluation set is calculated based on the analytic hierarchy process. The experiment results show that fuzzy comprehensive evaluation method is...
This paper proposes a dynamic tracking attention model (DTAM), which mainly comprises a motion attention mechanism, a convolutional neural network (CNN) and long short-term memory (LSTM), to recognize human action in a video sequence. In the motion attention mechanism, the local dynamic tracking is used to track moving objects in feature domain and global dynamic tracking corrects the motion in the...
Deep neural network (DNN) have become a popular means of separating a target source from a mixed signal. Most of DNN-based methods modify only the magnitude spectrum of the mixture. The phase spectrum is left unchanged, which is inherent in the short-time Fourier transform (STFT) coefficients of the input signal. However, recent studies have revealed that incorporating phase information can improve...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.