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An increasing demand of higher data rates in wireless communication forces the industry to look to higher frequencies to find the required bandwidths. This thesis is about analog transmitters in CMOS for millimeter-wave communication, and it focuses on improving power amplifiers and frequency generation circuits, and increase their efficiency. This thesis starts with an introduction to millimeter-

A convex envelope for the problem of finding the best approximation to a given matrix with a prescribed rank is constructed. This convex envelope allows the usage of traditional optimization techniques when additional constraints are added to the finite rank approximation problem. Expression for the dependence of the convex envelope on the singular values of the given matrix is derived and global

The hyperbolic Radon transform is a commonly used tool in seismic processing, for instance in seismic velocity analysis, data interpolation and for multiple removal. A direct implementation by summation of traces with different moveouts is computationally expensive for large data sets. In this paper we present a new method for fast computation of the hyperbolic Radon transforms. It is based on usi

In this paper we show how to convert the problem of estimating delay, slope and curvature of a parabolic event into a frequency estimation problem. Two dimensional data (time and offset) is converted into samples on a two-dimensional manifold embedded in a three-dimensional spaced. To conduct frequency estimation on this manifold we design general domain Hankel matrices and make use of a fixed poi

Ego-motion estimation is an important step towards fully autonomous mobile robots. In this paper we propose the use of an initial but automatic camera tilt calibration, which transforms the subsequent motion estimation to a 2D rigid body motion problem. This transformed problem is solved 2-optimally using RANSAC and a two-point method for rigid body motion. The method is experimentally evaluated u

Industrial robot systems being deployed today do not contain domain knowledge to aid robot operators in setup and operational use. To gather such knowledge in a robotic context requires mechanisms for entering and capturing semantic data. Such mechanisms would allow a system to gradually build a working vocabulary while interacting with the environment and operators, valuable for the bootstrapping

Student engagement is an important factor when it comes to the learning process. Students who do not feel engaged in their studies are more likely to fail their exams and might even drop out of their education. Different methods have been tried in order to increase student engagement. One of them is the contributing student pedagogy, where students contribute to the learning of others and also val

The devices that constitute the Internet of Things are evolving to include more than just enabling sensing and actuation over a wireless interface. In a contemporary scenario, these devices perform tasks and contribute to an aggregate information flow, in a distributed manner. In the wake of this evolution, new distributed Internet of Things frameworks have emerged. These frameworks maintain a dis

This brief presents an operational transconductance amplifier (OTA) linearization technique that is applied to a low-noise amplifier (LNA) and an OTA-C filter. Simulations show the effectiveness of the proposed technique on the LNA, whose noise and gain performance remain unaffected while the linearity is significantly improved. Measurements of the 80-MHz fourth order Butterworth OTA-C filter are

Conventional industrial robots are heavily dependent on hard automation that requires pre-specified fixtures and time-consuming (re)programming performed by experienced operators. In this work, teaching by human-only demonstration is used for reducing required time and expertise to setup a robotized assembly station. This is achieved by the proposed framework enhancing the robotic system with adva

One of the key challenges for structure from motion systems in order to make them robust to failure is the ability to handle outliers among the correspondences. In this paper we present two new algorithms that find the optimal solution in the presence of outliers when the camera undergoes a pure translation. The first algorithm has polynomial-time computational complexity, independently of the amo

Industrial robot systems being deployed today do not contain domain knowledge to aid robot operators in setup and operational use. To gather such knowledge in a robot context requires mechanisms for entering and capturing semantic data, that will gradually build a working vocabulary while interacting with environment and operators, for bootstrapping system knowledge and ensuring data collection ov

Interactive robots can benefit from learning from humans in situated communications, for instance in a guided tour, where the human user explains the environment to a mobile robot, or from being instructed to handle a specific task in an industrial setting. We have to assume that human users do not always give unambiguous or consistent information, which might result in inconsistent information be

An optimal soft multiple-input multiple-output (MIMO) detector is proposed with linear complexity for a general spatial multiplexing system with two transmitting symbols and NR ≥ 2 receiving antennas. The computational complexity of the proposed scheme is independent of the operating signal-tonoise ratio (SNR) and grows linearly with the constellation order. It provides the soft maximum-likelihood

This paper describes an algorithm to identify pleonastic pronouns using statistical techniques. The training step uses a coreference annotated corpus of English and focuses on a set of pronouns such as it. As far as we know, there is no corpus with a pleonastic annotation. The main idea of the algorithm was then to recast the definition of pleonastic pronouns as pronouns that never occur in a core