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We investigate the Compressed Sensing (CS) of digital signals with finite alphabets. More specifically, multiple-phase-shift-keying (M-PSK) alphabet is studied. Exploring the finite alphabets character, the sampling procedure can be achieved at Sub-Nyquist rate. Considering the modulation procedure, the model can also serve to a joint demodulation model. Furthermore, the sampling rate required here...
Feature based image matching is essential for many computer vision applications. Recently, progressive methods which iteratively enrich the candidate matches and reject the wrong ones have attracted a lot of attentions due to its high precision/recall and efficiency. Its quality of enrichment and rejection relies heavily on the accuracy of the estimated local affine transformation and the capability...
Automatic building change detection at different periods is very important for city monitoring, disaster assessment, map updating, etc. Some existing data sources could be used in this task such as 3D geometry model (e.g. Digital Surface Model, Geographic Information System) and radiometric images from satellites or special aircrafts. However, it is too expensive for timely change detection by using...
In specifications of Train Control System, the spatio-temporal requirement for trains executing actions is an important part. To model spatio-temporal changes about trains, we present a model language from another perspective in this paper. We adopt a function over a location set to define an action. In such a way, we can describe agent's spatial changes in executing action and can compute agent's...
Computed tomography angiography (CTA) allows for not only diagnosis of coronary artery disease (CAD) with high spatial resolution but also monitoring the remodeling of vessel walls in the progression of CAD. Alignment of coronary arteries in CTA images acquired at different times (with a 3–7 years interval) is required to visualize and analyze the geometric and structural changes quantitatively. Previous...
An end-pumped configuration is one of the most common laser structures at present. The filling factor provides the great effects on the laser performances, i.e., laser power, beam quality, pulse width, and output stability of an end-pumped laser. In this report, we systematically analyze the absorption characteristics, output power, and optical-optical efficiency by using a segmental accumulation...
In this paper, we propose a multi-manifold deep metric learning (MMDML) method for image set classification, which aims to recognize an object of interest from a set of image instances captured from varying viewpoints or under varying illuminations. Motivated by the fact that manifold can be effectively used to model the nonlinearity of samples in each image set and deep learning has demonstrated...
In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for large scale visual search. Unlike most existing binary codes learning methods which seek a single linear projection to map each sample into a binary vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the nonlinear relationship...
The classification of lower limb movement is important to the design of patient training or auxiliary force control system of moving robot. A lower limb gait classification algorithm using surface electromyography (sEMG) based on the particle swarm optimization process neural network (PSO-PNN) is proposed. Electromyography sensors are adopted to acquire the sEMG of four muscles around the knee joint...
3D information of real-world scenes provides important clues for many computer vision tasks. We present a simple but effective sliding camera system as well as a corresponding stereo reconstruction framework to retrieve 3D information of static scenes. By fusing geometric properties of the sliding camera system, our reconstruction algorithm achieves higher accuracy than conventional methods in quantitative...
Repetitive patterns exist widely in real world images, and matching images with plenty of repetitive patterns remains a challenging task. We present in this paper a novel feature matching algorithm of images with notably repetitive patterns, in which a reliable initial correspondence set is established, purified and propagated using a voting strategy, incorporating a local geometrical constraint....
The Nth Power Nonlinear Transformation (NPT) is a common method for automatic modulation classification, especially for PSK signals. However, greater than Nyquist rate sampling is essential for features extraction in NPT. In this paper, introducing the compressive sensing (CS) theory, we propose a novel Automatic Modulation Recognition (AMR) method based on the frequency spectrum of the Nth power...
Band-limited Volterra series model is an effective way for power amplifier (PA) modeling and digital predistortion (DPD), in the presence of limited DAC/ADC sampling rate. However, it suffers from the issue of requiring very high order baseband band-limiting filter to guarantee the model accuracy, which increases computational complexity drastically. This paper proposes a more efficient band-limited...
Sampling rate required in the Nth Power Nonlinear Transformation (NPT) method is typically much greater than Nyquist rate, which causes heavy burden for the Analog to Digital Converter (ADC). Taking advantage of the sparse property of PSK signals' spectrum under NPT, we develop the NPT method for PSK signals with Sub-Nyquist rate samples. In this paper, combined the NPT method with Compressive Sensing...
Reducing peak-to-average power ratio (PAPR) is an implementation challenge in orthogonal frequency division multiplexing (OFDM) systems. One way to reduce PAPR is to apply a set of selected partial transmission sequence (PTS) to the transmit signals. However, PTS selection is a highly complex NP-hard problem and the computational complexity is very high when a large number of subcarriers are used...
A high performance controller for magnetic suspension bearings is investigated. To improve the robustness of the controller and the suspension accuracy of the system, a fuzzy controller is designed using variable bandwidth triangle membership function. Considering the poor static-state performance of traditional fuzzy controllers, an additional linear extended state observer is introduced, which is...
Matching unknown latent fingerprints lifted from various objects or surfaces at crime scenes to fingerprints of known subjects is of vital importance for law enforcement agencies to identify suspects. Banknotes are one of the most common objects containing valuable latent fingerprints. However, due to the complex pattern printed on banknotes, it is a challenging problem even for human experts to mark...
Although minutia set based fingerprint matching algorithms have achieved good matching accuracy, developing a fingerprint recognition system that satisfies accuracy, efficiency and privacy requirements simultaneously remains a challenging problem. Fixed-length binary vector like IrisCode is considered to be an ideal representation to meet these requirements. However, existing fixed-length vector representations...
Kinship verification from facial images in wild conditions is a relatively new and challenging problem in face analysis. Several datasets and algorithms have been proposed in recent years. However, most existing datasets are of small sizes and one standard evaluation protocol is still lack so that it is difficult to compare the performance of different kinship verification methods. In this paper,...
Cloud computing is a promising technology to improve computational efficiency for both IT enterprise and individuals. Resource allocation in cloud computing is very challenging as both server computing power and network bandwidth are limited. The computational efficiency of cloud computing system can be significantly improved if the resources are allocated in a balanced fashion. However, resource...
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