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Spatially entangled photon states are used in experiments addressing fundamental properties of quantum mechanics as well as practical applications [1]. Thereby, the use of these states demands for time-saving detection mechanisms, capable of measuring coincidences between spatially separated photons with high spatial and temporal resolution. In this work, we demonstrate coincidence detection of spatially...
Heralded single photon sources are the subject of intense research owing to their usefulness in metrology and quantum information. These are often created using a pair of photons produced by spontaneous parametric downconversion (SPDC), from which one photon is used to certify the presence of the other. However, multiple-pair production and detector dark counts limit the quality of such sources. Here,...
The method for detecting radar signals which parameters are unknown and different from the reference signal is considered. The method is based on the correlation processing of signals from two components of the electromagnetic field.
We report a neural recording system with embedded lossless compression using spatiotemporal correlation and sparsity of neural signals to reduce dynamic power (Pd) dissipation for data transmission in high-density neural recording systems. We could successfully compress the data rate of neural signals by a factor of 5.35 (local field potential, LFP) and 10.54 (action potential, AP), respectively....
The quasi-likelihood algorithm detection of rectangle ultra-wideband quasi-radiosignal with unknown amplitude, initial phase and duration has been synthesized. The statistical characteristics of the efficiency synthesized detection algorithm — false alarm probability and probability of missing a signal, have been found.
We present a microwave measurement system for detection of dielectric objects in inhomogeneous powder flows in metal pipes. The system includes a non-intrusive microwave sensor that uses multiple cavity modes to measure the permittivity inside the pipe, and a fast-sampling microwave transmitter and receiver instrument. In this paper, we study a matched filter detection algorithm that takes temporal...
Digital image feature detection and matching is an important research content in the field of computer vision and pattern recognition. Inspired by Harris corner detector, the Harris correlation detector and Harris correlation descriptor (HCD) was studied and improved. In this paper, the scale adaptive Gaussian filter was introduced to optimize the descriptor and then the RANSAC algorithm was used...
True random number generators (TRNGs) are important hardware primitives required for many applications including cryptography, communication, and statistical simulation. This paper presents a TRNG with failure detection capability targeting cryptographic applications with a limited power budget. The proposed TRNG extracts entropy from latch comparators, whose metastable states are detected and encoded...
In this paper, we propose a digital restoration algorithm dealing with a one of the most common defect in archived video so-called blotches. TWo main modules compose the algorithm: blotches detection and removal. For the first module, we propose efficient blotches detection algorithm based on spatio-temporal information. This is done by using a temporal median filter applied on the adjacent frames...
Image registration which is frequently required in Medical, Computer vision and remote sensing field is used to align two images geometrically. This paper presents efficient method for providing speedup and more accuracy in compared to current state of the art existing methods. This paper focuses on Feature detection using Harris detector which gives best result based on performance and has firm invariance...
Canonical correlation analysis is a powerful statistical tool to measure the relationship between two sets of variables. This paper proposes an algorithm that combines multi-cycle cyclostationary spectrum sensing technique and the canonical correlation analysis tool. The proposed algorithm can be applied to both multiple antenna systems and single antenna systems. The probability of detection of this...
In this work, the inter-dependency of TCM signals is studied. Using this inter-dependency, correlation-based detectors are proposed for spectrum sensing of TCM signals in white Gaussian noise. In particular, a constant false alarm rate (CFAR) detector is presented and its performance is evaluated using simulations. We also describe an application of our detector for the classification of uncoded modulation...
A realistic stochastic multiple-input multiple-output (MIMO) channel is presented in this paper. It is shown that the spatial correlation depends on the statistical properties of the channel, the antenna pattern, the inter-element spacing and the array configuration. Furthermore, the total spatial correlation matrix is equal to the Kronecker product of the transmit and receive correlation matrices...
In this paper, an augmented registration approach towards Image stitching method is developed by examining the graciousness of feature based method jointly with direct based methods to identify and stitch a pair of overlapped images is presented. The developed method based on this hybrid approach is investigated in term of performance and accuracy. The ability of the examined method to classify overlapping...
Most of the existing quantum key distribution protocols do not consider the fact that the source and measuring device cannot be trusted, which causes hidden danger, such as the side channel attack, resulting in unsafe quantum communication. Therefore, it is important to research quantum key distribution protocol under the conditions of non-trusted device. We show a quantum key distribution protocol...
The methods of dynamic access to spectrum developed in Cognitive Radio require efficient and robust spectrum detectors. Most of these detectors suffer from four main limits: the computational cost required for the detection procedure; the need of prior knowledge of Primary User's (PU) signal features; the poor performances obtained in low SNR (Signal to Noise Ratio) environment; finding an optimal...
We extend earlier work by Essick et al. [1,2] with a study of similarities among sky localization maps corresponding to gravitational-wave transients. Earlier in 2016, the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) announced the first direct observation of gravitational waves from binary black holes [3,4]. Motivated by the fact that multiple detection and localization algorithms...
In this paper, we studied the massive multiple-input multiple-output (MIMO) system performance with N antenna users and streams can be multiplexed per each user. The spectral efficiency (SE) of uplink and downlink expressions is derived for any N antenna users and these achievable using estimated channels and per user basis minimum mean squared error successive interference cancellation (MMSE-SIC)...
Multi-label learning is widely applied in many tasks, where an object possesses multiple concepts with each represented by a class label. Previous studies on multi-label learning have focused on a fixed set of class labels, i.e., the class label set of test data is the same as that in the training set. In many applications, however, the environment is open and new concepts may emerge with previously...
Correlation-based algorithms are low-complexity spectrum sensing methods requiring little knowledge on primary signals or noise signals. However, their detection performance severely degrades in the low signal-to-noise ratio (SNR) regime with low signal correlation, which happens to be quite common in practice. In this paper, a weighted correlation- based spectrum sensing scheme and its simplified...
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