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This paper explores the use of fuzzy difference methods in order to understand the differences between forest classes. The context for this work is provided by REDD+, which seeks to reduce the net emissions of greenhouse gases by rewarding the conservation of forests in developing countries. REDD+ requires that local inventories of forest are undertaken and payments are made on the basis of the amount of forest (and associated carbon storage). At the most basic level this involves classifying land into forest and non-forest. However, the critical issues affecting the uptake, buy-in and ultimately the success of REDD+ are the lack of universally agreed definition of forest to support REDD+ mapping activities, and where such a definition is imposed, the marginalization of local community voices and local landscape conceptualizations. This tension is at the heart of REDD+. This paper addresses these issues by linking methods to quantify changes in fuzzy land cover to the concept of data primitives, which have been previously proposed as a suitable approach to move between land cover classes with different semantics. These are applied to case study that quantifies the difference in areas for two definitions of forest derived from the GLC and FAO definitions of forest. The results show how data primitives allow divergent concepts of forest to be represented and mapped from the same data and how the fuzzy sets approach can be used to quantify the differences and non-intersections of different concepts of forest. Together these methods provide for transparent translations between alternative conceptualizations of forest, allowing for plural notions of forest to be mapped and quantified. In particular, they allow for moving from an object-based notion of forest (and land cover in general) to a field-based one, entirely avoiding the need for forest boundaries.

This paper takes up the increasingly popular topic of drones — including Unmanned Aerial Vehicles (UAVs), small unmanned aerial Systems (sUAS), Remotely Piloted Aircraft (RPA) and a vast panoply of commercial drones and copters — to argue that our analysis should lie not so much on drones as objects, but as assemblages of the vertical. Drones, I argue, constitute a socio-technical assemblage of the sky and vertical space, which means that our focus should be not (only) on their technological development and capacities (although this is certainly important) but on their wider effects and affects. The latter of these include increasing algorithmic data collection and circulation. In the second part of the paper, I examine what I call "algorithmic governance" inspired by the recent governing algorithms conference at NYU but also drawing from Foucault's work on governmentality. Algorithmic governance constitutes "conduct of conduct" to modulate how "data shadows" or Deleuzian "dividuals" can be created, sold, and passed forward. My particular concern is how this takes place in a geographic register.

In this paper a method "Component Series Modeling" (CoSeMod) is presented. This allows fast and easy implementation of scalable model generations for passive component series based on measurement data or specification provided by manufacturer. These can be used in circuit models for fast EMC analysis and optimization, especially in frequency ranges where conducted emission and susceptibility dominate. EMC tasks require high precision equivalent circuit models of components. Models generated with CoSeMod provide in many cases as high a quality as original (static) models do. One feature of scalability is that new netlisting is not needed after component changes. The process of model creation is based on similarities of the components of the same model series (packaging, manufacturing process, material etcetera). Required equations of the relationship between nominal and parasitic values are calculated by nonlinear regression. Model generation for unknown components of a known series is possible with interpolation. Implementation is possible with relatively simple actions made in circuit simulator Saber. An EMC application example of the implemented model is also shown in this paper.

In this paper blind equalization algorithms based on digital watermarking are presented. Training sequence is sent along with the data in the form of watermark. Robust CDMA based watermarking algorithm is used to watermark the data. Watermark, which is spread over the data, does not consume extra bandwidth. So with the help of extracted watermark channel can be equalized just by using simple mean square algorithm. Two algorithms for equalization are proposed in this paper. In algorithm I the receiver does not require to know training sequence in advance. Using algorithm II, the sender does not require to send training sequence either, and data can still be equalized using simple LMS algorithm at low computational complexity.

This paper addresses issues related to the minimization of the computational burden in terms of both memory and speed during the simulation of electrical models. In order to achieve a simple and computational fast model the order reduction of its reducible part is proposed. In this paper the overview of the order reduction algorithms and their application are discussed. MEDEA+/A701 PARACHUTE BMBF/01M 3169 A BMBF/01M 3169 D BMBF/01M 3169 E

This paper deals with optimization of the received power profile for iterative parallel and successive interference cancellation (PIC/SIC) in coded CDMA systems. For practical implementation additional constraints should be applied. This paper focuses on the maximum tolerable bit error rate. It will be shown that optimized power profile can considerably gain the overall system performance. Due to unequal required receive powers an allocation to certain users can be done with respect to their individual power constraints. This is important especially in near-far scenarios. Beside these constraints also the maximum number of iterations is implemented due to limiting the computational complexity in the receiver.

With increasing radar activities in the automotive, industrial and private sector, there is a need to test radar sensors in their environment. A radar target simulator can help testing radar systems repeatably. In this paper, the authors present a concept of low-cost hardware for radar target simulation. The theoretical foundations are derived and analyzed. An implementation of a demonstrator operating in the 24 GHz ISM band is shown for which the dynamical range simulation was implemented in a FPGA with fast sampling ADCs and DACs. By using a FIR filtering approach a fine discretization of the range could be reached which will furthermore allow an inherent and automatic Doppler simulation by moving the target.

Short range inductive data transfer has become very popular in the last years with the increased interest in technologies like RFID and NFC. Additionally, wireless power transfer has been a field of intensive research and product development. In industrial applications, a combination of both is often needed to replace mechanical contacts, mainly for safety and reliability reasons, especially regarding spark prevention and maintenance reduction. In this paper, we present a compact inductive structure that can be implemented in an existing wireless energy transfer system. The structure is developed by field considerations, leading to a single structure comprising two signal ports that are decoupled from each other, but can be used to transfer a signal to a second structure of that kind with very small interference. An optimisation to achieve comparable channel characteristics is conducted by using 3-D field simulations. Subsequent measurements are conducted to verify the achieved performance.

The global Digital Elevation Model (DEM) resulting from the TanDEM-X mission provides information about the world topography with outstanding precision. In fact, performance analysis carried out with the already available data have shown that the global product is well within the requirements of 10 m absolute vertical accuracy and 2 m relative vertical accuracy for flat to moderate terrain. The mission's science phase took place from October 2014 to December 2015. During this phase, bistatic acquisitions with across-track separation between the two satellites up to 3.6 km at the equator were commanded. Since the relative vertical accuracy of InSAR derived elevation models is, in principle, inversely proportional to the system baseline, the TanDEM-X science phase opened the doors for the generation of elevation models with improved quality with respect to the standard product. However, the interferometric processing of the large-baseline data is troublesome due to the increased volume decorrelation and very high frequency of the phase variations. Hence, in order to fully profit from the increased baseline, sophisticated algorithms for the interferometric processing, and, in particular, for the phase unwrapping have to be considered. This paper proposes a novel dual-baseline region-growing framework for the phase unwrapping of the large-baseline interferograms. Results from two experiments with data from the TanDEM-X science phase are discussed, corroborating the expected increased level of detail of the large-baseline DEMs.

In this paper, we present a method to increase the time resolution of a pulse width modulator by using delay lines. The modulator is part of an open loop class D power amplifier, which uses the ZePoC algorithm to code the audio signal which is amplified in the class D power stage. If the time resolution of the pulse width modulator is high enough, ZePoC could also be used to build an high accuracy AC power standard, because of its open loop property. With the presented method the time resolution theoretically could be increased by a factor of 16, which means here the time resolution will be enhanced from 5 ns to 312.5 ps.

This paper investigates the impact of an error-prone buffer memory on a channel decoder as employed in modern digital communication systems. On one hand this work is motivated by the fact that energy efficient decoder implementations may not only be achieved by optimizations on algorithmic level, but also by chip-level modifications. One of such modifications is so called aggressive voltage scaling of buffer memories, which, while achieving reduced power consumption, also injects errors into the likelihood values used during the decoding process. On the other hand, it has been recognized that the ongoing increase of integration density with smaller structures makes integrated circuits more sensitive to process variations during manufacturing, and to voltage and temperature variations. This may lead to a paradigm shift from 100 %-reliable operation to fault tolerant signal processing. Both reasons are the motivation to discuss the required co-design of algorithms and underlying circuits. For an error-prone receive buffer of a Turbo decoder the influence of quantizer design and index assignment on the error resilience of the decoding algorithm is discussed. It is shown that a suitable design of both enables a compensation of hardware induced bits errors with rates up to 1 % without increasing the computational complexity of the decoder.

A new kind of a modular multi-purpose robot system is developed to measure the spatial field distributions of very large as well as of small and crowded areas. The probe is automatically placed at a number of pre-defined positions where measurements are carried out. The advantages of this system are its very low influence on the measured field as well as its wide area of possible applications. In addition, the initial costs are quite low. In this paper the theory underlying the measurement principle is explained. The accuracy is analyzed and sample measurements are presented.

This paper describes the application of an adaptive complexity decoder for the Long Term Evolution (LTE) downlink Turbo code. The proposed decoding approach is based on the block syndrome decoding principle and enables adaptive reduction of decoding effort depending on current SNR and iteration number with negligible influence on decoding performance. Numerical results in context of LTE downlink using typical mobile channels are used to demonstrate the efficiency of the approach.

This paper presents a physical (PHY) layer simulator of the IEEE 802.11p standard for Wireless Access in Vehicular Environments (WAVE). This simulator allows the emulation of data transmission via different radio channels as well as the analysis of the resulting system behavior. The PHY layer simulator is part of an integrated simulation platform including a traffic model to generate realistic mobility of vehicles and a 3D ray-optical model to calculate the multipath propagation channel between transmitter and receiver. Besides deterministic channel modeling by means of ray-optical modeling, the simulator can also be used with stochastic channel models of typical vehicular scenarios. With the aid of this PHY layer simulator and the integrated channel models, the resulting performance of the system in terms of bit and packet error rates of different receiver designs can be analyzed in order to achieve a robust data transmission.

The development of a non- destructive measurement method for ion beam parameters has been treated in various projects. Although results are promising, the high complexity of beam dynamics has made it impossible to implement a real time process control up to now. In this paper we will propose analysing methods based on the dynamics of Cellular Nonlinear Networks (CNN) that can be implemented on pixel parallel CNN based architectures and yield satisfying results even at low resolutions.

The increasing availability of both static and dynamic context information has steadily been driving the development of context-aware communication systems. Adapting system behavior according to current context of the network, the user, and the terminal can yield significant end-to-end performance improvements. In this paper, we present a concept for how to use context information, in particular location information and movement prediction, for Heterogeneous Access Management (HAM). In a first step, we outline the functional architecture of a distributed and extensible context management system (CMS) that defines the roles, tasks, and interfaces of all modules within such a system for large-scale context acquisition and dissemination. In a second step, we depict how the available context information can be exploited for optimizing terminal handover decisions to be made in a multi-RAT (radio access technology) environment. In addition, the utilized method for predicting terminal location as well as the objective functions used for evaluating and comparing system performance are described. Finally, we present preliminary simulation results demonstrating that HAM systems that include current and future terminal context information in the handover decision process clearly outperform conventional systems.

Dieser Beitrag behandelt die Abbildung eines videobasierten Verfahrens zur echtzeitfähigen Auswertung von Winkelhistogrammen auf eine modulare Coprozessor-Architektur. Die Architektur besteht aus mehreren dedizierten Recheneinheiten zur parallelen Verarbeitung rechenintensiver Bildverarbeitungsverfahren und ist mit einem RISC-Prozessor verbunden. Eine konfigurierbare Architekturerweiterung um eine Recheneinheit zur Auswertung von Winkelhistogrammen von Objekten ermöglicht in Verbindung mit dem RISC eine echtzeitfähige Klassifikation. Je nach Konfiguration sind für die Architekturerweiterung auf einem Xilinx Virtex-5-FPGA zwischen 3300 und 12 000 Lookup-Tables erforderlich. Bei einer Taktfrequenz von 100 MHz können unabhängig von der Bildauflösung pro Einzelbild in einem 25-Hz-Videodatenstrom bis zu 100 Objekte der Größe 256×256 Pixel analysiert werden. This paper presents the mapping of a video-based approach for real-time evaluation of angular histograms on a modular coprocessor architecture. The architecture comprises several dedicated processing elements for parallel processing of computation-intensive image processing tasks and is coupled with a RISC processor. A configurable architecture extension, especially a processing element for evaluating angular histograms of objects in conjunction with a RISC processor, provides a real-time classification. Depending on the configuration of the architecture extension, 3 300 to 12 000 look-up tables are required for a Xilinx Virtex-5 FPGA implementation. Running at a clock frequency of 100 MHz and independently of the image resolution per frame, 100 objects of size 256×256 pixels are analyzed in a 25 Hz video stream by the architecture.

In this paper we explore different hardware accelerators for cryptography based on elliptic curves. Furthermore, we present a hierarchical multiprocessor system-on-chip (MPSoC) platform that can be used for fast integration and evaluation of novel hardware accelerators. In respect of two application scenarios the hardware accelerators are coupled at different hierarchy levels of the MPSoC platform. The whole system is implemented in a state of the art 65 nm standard cell technology. Moreover, an FPGA-based rapid prototyping system for fast system verification is presented. Finally, a metric to analyze the resource efficiency by means of chip area, execution time and energy consumption is introduced.

An increasing number of modern applications and services is based on the knowledge of the users actual position. Depending on the application a rough position estimate is sufficient, e. g. services in cellular networks that use the information about the users actual cell. Other applications, e. g. navigation systems use the GPS-System for accurate position finding. Beyond these outdoor applications a growing number of indoor applications requires position information. The previously mentioned methods for position finding (mobile cell, GPS) are not usable for these indoor applications. Within this paper we will present a system that relies on the simultaneous measurement of doppler signals at four different positions to obtain position and velocity of an unknown object. It is therefore suiteable for indoor usage, extendig already existing wireless infrastructure.

This paper presents two Cordic based algorithms which may be used for digital baseband processing in OFDM and/or CDMA based communication systems. The first one is a linear least squares based multiuser detector for CDMA incorporating descrambling and despreading. The second algorithm is a pure Cordic based FFT implementation. Both algorithms can be implemented using solely Cordic based architectures (e.g. coprocessors or ASIPs). The algorithms exactly fit the needs of a multistandard terminal as they both are freely parameterizable. This regards to the accuracy of the results as well as to the parameters of the performed function (e.g. size of the FFT).

In this paper a method to obtain harmonic transfer matrices (HTM) from simulated or measured values (signature & signature response) is presented. These matrices subserve a description of complex systems (e.g. RF front-ends) with real properties, which can't be specified by simple analytic expressions. They afford to give statements about a systems parameter. That's why HTM are suitable for Built-In-Self-Test (BIST) and opens the option for Built-In-Self-Correction (BISC) for critical function-blocks.

A BIST scheme for testing on chip DAC is presented in this paper. We discuss the generation of on chip testing stimuli and the measurement of digital signals with a narrow-band digital filter. We validate the scheme with software simulation and point out the possibility of ADC BIST with verified DACicus-journals.

In this paper, an automatic near-real time (NRT) flood detection approach is presented, which combines histogram thresholding and segmentation based classification, specifically oriented to the analysis of single-polarized very high resolution Synthetic Aperture Radar (SAR) satellite data. The challenge of SAR-based flood detection is addressed in a completely unsupervised way, which assumes no training data and therefore no prior information about the class statistics to be available concerning the area of investigation. This is usually the case in NRT-disaster management, where the collection of ground truth information is not feasible due to time-constraints. A simple thresholding algorithm can be used in the most of the cases to distinguish between "flood" and "non-flood" pixels in a high resolution SAR image to detect the largest part of an inundation area. Due to the fact that local gray-level changes may not be distinguished by global thresholding techniques in large satellite scenes the thresholding algorithm is integrated into a split-based approach for the derivation of a global threshold by the analysis and combination of the split inherent information. The derived global threshold is then integrated into a multi-scale segmentation step combining the advantages of small-, medium- and large-scale per parcel segmentation. Experimental investigations performed on a TerraSAR-X Stripmap scene from southwest England during large scale flooding in the summer 2007 show high classification accuracies of the proposed split-based approach in combination with image segmentation and optional integration of digital elevation models.