A New Radar Detector in Unknown Signal and Clutter Environment

2006 ◽  
Author(s):  
B.A. Bastami ◽  
H. Amindavar
Keyword(s):  
Unknown Signal

scholarly journals Gonadotropin-Releasing Hormone Inhibits Ether-à-Go-Go-Related Gene K+ Currents in Mouse Gonadotropes

Endocrinology ◽  
2010 ◽  
Vol 151 (3) ◽  
pp. 1079-1088 ◽  
Author(s):  
Wiebke Hirdes ◽  
Crenguta Dinu ◽  
Christiane K. Bauer ◽  
Ulrich Boehm ◽  
Jürgen R. Schwarz
Keyword(s):  
Resting Potential ◽  
Related Gene ◽  
Activation Curve ◽  
Signal Cascade ◽  
Primary Mouse ◽  
Voltage Dependent ◽  
K Current ◽  
Unknown Signal ◽  
Ca2 Channels ◽  
K Currents

Secretion of LH from gonadotropes is initiated by a GnRH-induced increase in intracellular Ca2+ concentration ([Ca2+]i). This increase in [Ca2+]i is the result of Ca2+ release from intracellular stores and Ca2+ influx through voltage-dependent Ca2+ channels. Here we describe an ether-à-go-go-related gene (erg) K+ current in primary mouse gonadotropes and its possible function in the control of Ca2+ influx. To detect gonadotropes, we used a knock-in mouse strain, in which GnRH receptor-expressing cells are fluorescently labeled. Erg K+ currents were recorded in 80–90% of gonadotropes. Blockage of erg currents by E-4031 depolarized the resting potential by 5–8 mV and led to an increase in [Ca2+]i, which was abolished by nifedipine. GnRH inhibited erg currents by a reduction of the maximal erg current and in some cells additionally by a shift of the activation curve to more positive potentials. In conclusion, the erg current contributes to the maintenance of the resting potential in gonadotropes, thereby securing a low [Ca2+]i by restricting Ca2+ influx. In addition, the erg channels are modulated by GnRH by an as-yet unknown signal cascade.

scholarly journals Coupling Planar Cell Polarity Signaling to Morphogenesis

2002 ◽  
Vol 2 ◽  
pp. 434-454 ◽  
Author(s):  
Jeffrey D. Axelrod ◽  
Helen McNeill
Keyword(s):  
Cell Polarity ◽  
Planar Cell Polarity ◽  
Fruit Fly ◽  
Convergent Extension ◽  
Cytoskeletal Reorganization ◽  
Directional Information ◽  
Cochlear Hair Cell ◽  
Cellular Asymmetry ◽  
Pcp Signaling ◽  
Unknown Signal

Epithelial cells and other groups of cells acquire a polarity orthogonal to their apical–basal axes, referred to as Planar Cell Polarity (PCP). The process by which these cells become polarized requires a signaling pathway using Frizzled as a receptor. Responding cells sense cues from their environment that provide directional information, and they translate this information into cellular asymmetry. Most of what is known about PCP derives from studies in the fruit fly,Drosophila. We review what is known about how cells translate an unknown signal into asymmetric cytoskeletal reorganization. We then discuss how the vertebrate processes of convergent extension and cochlear hair-cell development may relate toDrosophilaPCP signaling.

Ensuring the secrecy of the radar

2021 ◽  
Author(s):  
S.G. Vorona ◽  
S.N. Bulychev
Keyword(s):  
Likelihood Function ◽  
Radio Pulse ◽  
A Priori ◽  
Detection Threshold ◽  
Posteriori Probability ◽  
Echo Signal ◽  
A Posteriori Probability ◽  
Advantages And Disadvantages ◽  
Radio Electronic ◽  
Unknown Signal

The article deals with the issue of stealth of radio-electronic means, energy and structural, radio-electronic masking and ways of its implementation. The structure of the unknown signal for exploration and its parameters, as well as the a posteriori probability of each signal associated with the a priori likelihood function and the cases of its solution. The advantages and disadvantages of broadband signals and their characteristics used in modern radars are considered. On the basis of which conclusions are drawn: LFM radio pulse and a single FCM pulse, used in target tracking modes, has high resolution capabilities in range and radial velocity. The ACF of the FCM pulse has side lobes that raise the target detection threshold, as a result of which radar targets with a weak echo signal can be missed. The considered signals do not provide energy and structural stealth of the radar operation.

scholarly journals GARLM: Greedy Autocorrelation Retrieval Levenberg–Marquardt Algorithm for Improving Sparse Phase Retrieval

2018 ◽  
Vol 8 (10) ◽  
pp. 1797 ◽  
Author(s):  
Zhuolei Xiao ◽  
Yerong Zhang ◽  
Kaixuan Zhang ◽  
Dongxu Zhao ◽  
Guan Gui
Keyword(s):  
Fourier Transform ◽  
Local Search ◽  
Phase Retrieval ◽  
Greedy Algorithms ◽  
Optimal Estimation ◽  
Retrieval Algorithm ◽  
Marquardt Algorithm ◽  
Levenberg Marquardt ◽  
Local Search Procedure ◽  
Unknown Signal

The goal of phase retrieval is to recover an unknown signal from the random measurements consisting of the magnitude of its Fourier transform. Due to the loss of the phase information, phase retrieval is considered as an ill-posed problem. Conventional greedy algorithms, e.g., greedy spare phase retrieval (GESPAR), were developed to solve this problem by using prior knowledge of the unknown signal. However, due to the defect of the Gauss–Newton method in the local convergence problem, especially when the residual is large, it is very difficult to use this method in GESPAR to efficiently solve the non-convex optimization problem. In order to improve the performance of the greedy algorithm, we propose an improved phase retrieval algorithm, which is called the greedy autocorrelation retrieval Levenberg–Marquardt (GARLM) algorithm. Specifically, the proposed GARLM algorithm is a local search iterative algorithm to recover the sparse signal from its Fourier transform magnitude. The proposed algorithm is preferred to existing greedy methods of phase retrieval, since at each iteration the problem of minimizing the objective function over a given support is solved by using the improved Levenberg–Marquardt (ILM) method and matrix transform. A local search procedure such as the 2-opt method is then invoked to get the optimal estimation. Simulation results are given to show that the proposed algorithm performs better than the conventional GESPAR algorithm.

Rao and Wald Tests for Distributed Targets Detection With Unknown Signal Steering

2013 ◽  
Vol 20 (11) ◽  
pp. 1086-1089 ◽  
Author(s):  
Weijian Liu ◽  
Wenchong Xie ◽  
Yongliang Wang
Keyword(s):  
Wald Tests ◽  
Unknown Signal
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