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The identification of accurate disturbance models from data has application both to estimator design and controller performance monitoring. Methods to find the disturbance model include maximum likelihood estimation, Bayesian estimation, covariance matching, correlation techniques (such as autocovariance least-squares), and subspace identification methods. Here we formulate a maximum likelihood estimation...
In this paper, we propose a new method of secrecy signal and artificial noise (AN) transmission for a MISO wiretap channel in wireless cellular networks. We first design the secrecy signal beamformer such that its power leakage to the unintended directions is minimized, then we concentrate the AN on the directions with higher risk of information leakage, rather than broadcast it isotropically, such...
We consider the control of two UAVs tracking an evasive moving ground vehicle. The UAVs are small fixed-wing aircraft equipped with gimbaled cameras and must coordinate their control actions so that at least one UAV is always close to the target. The control actions of the UAVs are computed based on noisy measurements of the UAVs' current state and vision-based measurements of the target's position...
A convex optimization based approach is presented to perform model-data assimilation of spatial temporal dynamical systems where sensor error characteristics are not available. The key idea of the proposed technique is that one should not make any assumption regarding the statistical properties of sensor data when they are not available. Recently developed quadrature scheme, Conjugate Unscented Transformation...
We compare two iterative frequency domain sub-space identification methods using nuclear norm minimization to more commonly used non-iterative methods by means of an artificially created test problem involving very noisy uniformly spaced frequency data. The two corresponding optimization problems are motivated and their first-order algorithmic solutions based on the alternating direction method of...
Incorporation of user feedback in enterprise management products can greatly enhance our understanding of modern technology challenges and amplify the ability for those products to home in to user environments. In this paper we present an entropy-based confidence determination approach to process user feedback data (direct or indirect) to automatically rank and update the beliefs of any recommender...
SAR images have distinctive characteristics compared to optical images: speckle phenomenon produces strong fluctuations, and strong scatterers have radar signatures several orders of magnitude larger than others. We propose to use an image decomposition approach to account for these peculiarities. Several methods have been proposed in the field of image processing to decompose an image into components...
We investigate the dependence of maximum system reach on symbol rate. We identify a suitable modeling framework and derive a closed-form formula for the optimum rate, typically 2-to-10 GBaud. Maximum reach gains are between 5% and 20%.
Accurate and consistent ego motion estimation is a critical component of autonomous navigation. For this task, the combination of visual and inertial sensors is an inexpensive, compact, and complementary hardware suite that can be used on many types of vehicles. In this work, we compare two modern approaches to ego motion estimation: the Multi-State Constraint Kalman Filter (MSCKF) and the Sliding...
This paper reports a demonstration of high speed visible light communications using a blue laser diode combined with a remote phosphor. This method both generates white light and supports multi Gb/s communications. Data rates of up to 5.62 Gb/s and 6.52 Gb/s were achieved by using OFDM with fixed-rate and adaptive loading approaches, respectively. A total data rate of 10 Gb/s was found to be achievable...
A fully integrated low power LNA is implemented using 65-nm RF CMOS technology for 2.14-GHz band. By taking the advantage of higher transition frequency of recent technologies, transistors are biased in the moderate inversion region and this permitted scaling down the supply voltage to 0.7 V. Further, the exploration of design spaces from strong to weak inversion led to the development of a low power...
In this paper, joint sensor localization and synchronization in non-cooperative wireless sensor networks (WSNs) using time-of-arrival (TOA) measurements is studied. In addition to zero-mean errors in TOA measurements we consider other sources of error such as non-line-of-sight (NLOS) propagation and anchor uncertainty to make our technique more useful in practice, where the presence of these errors...
Due to its psychological and physiological interpretation of naturally occurring data, Nonnegative Matrix Factorization (NMF) has attracted considerable attention for learning effective representation for images. And its graph-regularized extensions have shown promising results by exploiting the low dimensional manifold structure of data. Actually, their performance can be further improved because...
Recently, the precise performance of the Generalized LASSO algorithm for recovering structured signals from compressed noisy measurements, obtained via i.i.d. Gaussian matrices, has been characterized. The analysis is based on a framework introduced by Stojnic and heavily relies on the use of Gordon's Gaussian min-max theorem (GMT), a comparison principle on Gaussian processes. As a result, corresponding...
This work investigates the joint design of fronthaul compression and precoding for the downlink of Cloud Radio Access Networks (C-RANs). The main goal is that of bringing insight into an aspect of the optimal functional split between Radio Units (RUs) and Central Unit (CU), namely: where should precoding be performed? Unlike previous works, we tackle this issue for a practical scenario with block-ergodic...
For single-antenna Gaussian interference channels, we re-formulate the problem of determining the Generalized Degrees of Freedom (GDoF) region achievable by treating interference as noise (TIN) with proper power control from a combinatorial optimization perspective. We show that the TIN power control problem can be cast into an assignment problem, such that the globally optimal power allocation variables...
The main usage of cellular networks has changed from voice to data traffic, mostly requested by static users. In this paper, we analyze how a cellular network should be designed to provide such wireless broadband access with maximal energy efficiency (EE). Using stochastic geometry and a detailed power consumption model, we optimize the density of access points (APs), number of antennas and users...
This paper presents a design methodology for power optimized neural frontend interfaces (NFIs). The minimum power is analytically derived based on the constituent building blocks of the NFI, namely low noise amplifier, programmable gain amplifier and analog-to-digital converter (ADC), all of which are bound by noise. In the optimization process two types of ADC are considered: the successive approximation...
The optimization problem of error-feedback and realization to minimize the roundoff noise in a closed-loop system with full-order state observer feedback subject to l2-scaling constraints is investigated. It is shown that joint optimization of error-feedback and realization is not needed when utilizing a general-matrix error-feedback loop because the optimal error-feedback matrix, in closed-form,...
Sparse bundle adjustment (SBA) is the state of the art method for simultaneously optimizing a set of camera poses and 3D points. The multibody bundle adjustment optimizes the static scene and the moving rigid object(s). The result is one camera path representing the main camera motion and virtual camera path(s) for each of the independently moving objects in the scene. The bundle adjustment for the...
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