Filetype
We analyze the local convergence of proximal splitting algorithms to solve optimization problems that are convex besides a rank constraint. For this, we show conditions under which the proximal operator of a function involving the rank constraint is locally identical to the proximal operator of its convex envelope, hence implying local convergence. The conditions imply that the non-convex algorith
Cloud computing infrastructures are powering most of the web hosting services that we use at all times. A recent failure in the Amazon cloud infrastructure made many of the website that we use on a hourly basis unavailable1. This illustrates the importance of cloud applications being able to absorb peaks in workload, and at the same time to tune their power requirements to the power and energy cap
In this paper we consider L1 optimal and H-infinity optimal control problems for a particular class of Positive Bilinear Systems that arise in drug dosage design for HIV treatment. Starting from existent characterizations of the L1-norm for positive systems, a convex formulation for the first problem is provided. As for the H-infinity case, we propose an algorithm based on the iterative solution o
In the framework of robotics, Reinforcement Learning (RL) deals with the learning of a task by the robot itself. This paper presents a hierarchical planning approach in which the robot learns the optimal behavior for different levels. For high-level discrete actions, Q-learning was chosen, whereas for the low level we utilize Policy Improvement with Path Integrals (PI^2) algorithm to learn the par
This work presents a 2.0mm2 128×16 massive MIMO detector IC that provides 21dB array gain and 16x multiplexing gain at the system level. The detector implements iterative expectation-propagation detection (EPD) for up to 256-QAM modulation. Tested with measured channel data [1], the detector achieves 4.3dB processing gain over state-of-the-art massive MlMo detectors [2, 3], enabling 2.7x reduction
The purpose of this paper is to analyse transient dynamics in adaptive control using statistical concentration bounds. For maximal clarity, the study is limited to a linear first order system with a single uncertain parameter. Two types of bounds are given: First we prove probabilistic bounds on the parameter estimation error as a function of time. In particular, we prove that the estimation error
Forward–backward and Douglas–Rachford splitting are methods for structured nonsmooth optimization. With the aim to use smooth optimization techniques for nonsmooth problems, the forward–backward and Douglas–Rachford envelopes where recently proposed. Under specific problem assumptions, these envelope functions have favorable smoothness and convexity properties and their stationary points coincide
We consider the problem of finding an event-based sampling scheme that optimizes the trade-off between average sampling rate and control performance in a linear-quadratic-Gaussian (LQG) control problem setting with output feedback. Our analysis is based on a recently presented sampled-data controller structure, which remains LQG-optimal for any choice of sampling scheme. We show that optimization
This paper describes a method to compute frame size estimates to be used in quasi Worst-Case Transmission Times (qWCTT) for cameras that transmit frames over IP-based communication networks. The precise determination of qWCTT allows us to model the network access scheduling problem as a multiframe problem and to re-use theoretical results for network scheduling. The paper presents a set of experim
Innovation and entrepreneurship are essential processes for human development, market growth, and technological breakthroughs, and it is vital for economic growth. Despite its importance, innovation is inherently difficult to measure and hence it is almost impossible for an individual or organization to know how they can improve their innovation output or claim that they are great at innovation. T
The area of Internet of Things (IoT) is growing and it affects a large amount of users, which means that security is important. Many parts of IoT systems are built with Open Source Software, for which security vulnerabilities are available. It is important to update the software when vulnerabilities are detected, but it is unclear to what extent this is done in industry today. This study presents
We consider model order reduction of stable linear systems which leave ellipsoidal cones invariant. We show how balanced truncation can be modified to preserve cone- invariance. Additionally, this implies a method to perform external positivity preserving model reduction for a large class of systems.
Industrial robots typically require detailed programming and carefully configured work cells to perform well. The large engineering effort implicates high cost and long preparation time, and this is the major obstruction when mediating tasks to robots. The research in this thesis therefore aims to make robot programming faster and more accessible. Methods that allow for programmers to mediate and
This document outlines how to setup and run computations in parallel using Julia on a collection of remote computers, such as computers in a university lab. After the environment has been setup,Only minor modifications to serially executed code is necessary to enable parallel execution.Written for Julia version 1.0
We describe how to utilize the possibility of differentiating through arbitrary Julia codeto perform tasks such as controller optimization. The user specifies a cost function, forexample, the integrated squared error between output and reference, and constraints, suchas a maximum acceptable value of the sensitivity function. Julia performs the integrationand calculates the sensitivities of the cos
This paper presents an injection-locked 65-nm CMOS circuit that upconverts and power amplifies baseband signals to RF. The circuit delivers an RF output power of 28.7 dBm, with a power gain and maximum power added efficiency (PAE) of 20.6 dB and 68.1%, respectively. Both AM–AM-conversion and AM–PM-conversion are low, less than 1 dB and 1°, respectively, resulting in an EVM of 4.7% for Long Term Ev
We present two sensitivity function trade-offs that apply to a class of networks with a string topology. In particular we show that a lower bound on the H-infinity norm and a Bode sensitivity relation hold for an entire family of sensitivity functions associated with growing the network. The trade-offs we identify are a direct consequence of growing the network, and can be used to explain why poor
We consider least-squares approximation of a function of one variable by a continuous, piecewise-linear approximand that has a small number of breakpoints. This problem was notably considered by Bellman who proposed an approximate algorithm based on dynamic programming. Many suboptimal approaches have been suggested, but so far, the only exact methods resort to mixed integer programming with super
