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We consider the problem of designing demodulators for channels with memory that use reduced-size trellis descriptions for the received signal. We assume an overall iterative receiver, and for the parts of the signal not covered by the trellis description, we use interference cancellation based on the soft information provided by the outer decoder. In order to reach a trellis description, a linear

Event-based sensing and communication holds the promise of lower resource utilization and/or better performance for remote state estimation applicationsin e.g networked control systems (NCS). However, the problem of designing an optimal event-based state estimator often becomes untractable due to nonlinear measurements. This complexity is avoided with stochastic event-triggering. In this work, we

We consider the problem of localizing a novel image in a large 3D model, given that the gravitational vector is known. In principle, this is just an instance of camera pose estimation, but the scale of the problem introduces some interesting challenges. Most importantly, it makes the correspondence problem very difficult so there will often be a significant number of outliers to handle. To tackle

The McEliece public key cryptosystem is an attractive general construction that has received extensive attention over the years. Recently, a very promising version called QC-MDPC, was proposed. By using binary quasi-cyclic codes, the size of the public key can be decreased significantly. The decryption step involves iterative decoding of moderate density parity check codes (MDPC). In this paper we

In computer vision, many problems can be formulated as finding a low rank approximation of a given matrix. Ideally, if all elements of the measurement matrix are available, this is easily solved in the L2-norm using factorization. However, in practice this is rarely the case. Lately, this problem has been addressed using different approaches, one is to replace the rank term by the convex nuclear no

Automation programming is typically done using blocks and dataflow connections, in diagram languages that support user-defined block types. Often, these types are intended to be instantiated and connected to other blocks in common patterns, corresponding to anticipated variability. We present the new language mechanisms of wirings and recommendations that allow these intentions to be encoded as fe

Many modern software applications have performance requirements, like mobile and embedded systems that must keep up with sensor data, or web services that must return results to users within an acceptable latency bound. For such applications, the goal is not to run as fast as possible, but to meet their performance requirements with minimal resource usage, the key resource in most systems being en

We consider a multiple-input multiple-output (MIMO) channel with inter-symbol interference (ISI) where signal detection is highly complex due to the large signal state-space dimensionality. A common strategy is to apply a front-end filter (FEF) to eliminate the ISI dimension (i.e. full ISI equalization). This FEF is then followed by a frequency non-selective MIMO detector. However, another, much l

Mathematical optimization is becoming increasingly important for engineering in general and control in particular. This thesis deals with numerical methods, primarily direct collocation, and symbolic methods, primarily block-triangular ordering and tearing, for numerical solution of general dynamic optimization problems involving dynamical systems modeled by large-scale differential-algebraic equa

This work presents a digital calibration technique in continuous-time (CT) delta-sigma (Δ Σ) analog to digital converter. The converter is clocked at 144 MHz with a low oversampling ratio (OSR) of only 8. Dynamic element matching is not efficient to linearize the digital to analog converter (DAC) when the OSR is very low. Therefore, non-idealities in the outermost multi-bit feedback DAC are measur

The trend in cellular chipset design today is to incorporate support for a larger number of frequency bands for each new chipset generation. If the chipset also supports receiver diversity two low noise amplifiers (LNAs) are required for each frequency band. This is however associated with an increase of off-chip components, i.e. matching components for the LNA inputs, as well as complex routing o

Decision making and requirements scoping occupy central roles in helping to develop products that are demanded by the customers and ensuring company strategies are accurately realized in product scope. Many companies experience continuous and frequent scope changes and fluctuations but struggle to measure the phenomena and correlate the measurement to the quality of the requirements process. We pr

We present the PalCom Object Notation, a textual data representation format for communication between internet of things which support binary and textual data. The format does not require parsing of user data (or the “payload”) and is thus efficient to use also for large binary values such as digital images, audio and video as well as for short textual values. These can be mixed in the same messag

This paper presents a link adaptive processor to perform low-complexity channel estimation and QR decomposition (QRD) in Long Term Evolution-Advanced (LTE-A) receivers. The processor utilizes frequency domain correlation of the propagation channel to adaptively avoid unnecessary computations in the received signal processing, achieving significant complexity reduction with negligible performance l

We propose a novel approach to the problem of inverse kinematics for possibly redundant planar manipulators. We show that, by considering the joints as point masses in a fictitious gravity field, and by adding proper constraints to take into account the length of the links, the kinematic inversion may be cast as a convex programming problem. Convex constraints in the decision variables (in particu

The problem of synthesizing network-decentralized observers arises when several agents, corresponding to the nodes of a network, exchange information about local measurements to asymptotically estimate their own state. The network topology is unknown to the nodes, which can rely on information about their neighboring nodes only. For homogeneous systems, composed of identical agents, we show that a

We address H-infinity state feedback and give a simple form for an optimal control law applicable to linear time invariant systems with symmetric and Hurwitz state matrix. More specifically, the control law as well as the minimal value of the norm can be expressed in the matrices of the system's state space representation, given separate cost on state and control input. Thus, the control law is tr