Strategies for neural networks in ballistocardiography with a view towards hardware implementation

A thesis submitted for the degree of Doctor of Philosophy at the University of LutonThe work described in this thesis is based on the results of a clinical trial conducted by the research team at the Medical Informatics Unit of the University of Cambridge, which show that the Ballistocardiogram (BCG) has prognostic value in detecting impaired left ventricular function before it becomes clinically overt as myocardial infarction leading to sudden death. The objective of this study is to develop and demonstrate a framework for realising an on-line BCG signal classification model in a portable device that would have the potential to find pathological signs as early as possible for home health care. Two new on-line automatic BeG classification models for time domain BeG classification are proposed. Both systems are based on a two stage process: input feature extraction followed by a neural classifier. One system uses a principal component analysis neural network, and the other a discrete wavelet transform, to reduce the input dimensionality. Results of the classification, dimensionality reduction, and comparison are presented. It is indicated that the combined wavelet transform and MLP system has a more reliable performance than the combined neural networks system, in situations where the data available to determine the network parameters is limited. Moreover, the wavelet transfonn requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced. Overall, a methodology for realising an automatic BeG classification system for a portable instrument is presented. A fully paralJel neural network design for a low cost platform using field programmable gate arrays (Xilinx's XC4000 series) is explored. This addresses the potential speed requirements in the biomedical signal processing field. It also demonstrates a flexible hardware design approach so that an instrument's parameters can be updated as data expands with time. To reduce the hardware design complexity and to increase the system performance, a hybrid learning algorithm using random optimisation and the backpropagation rule is developed to achieve an efficient weight update mechanism in low weight precision learning. The simulation results show that the hybrid learning algorithm is effective in solving the network paralysis problem and the convergence is much faster than by the standard backpropagation rule. The hidden and output layer nodes have been mapped on Xilinx FPGAs with automatic placement and routing tools. The static time analysis results suggests that the proposed network implementation could generate 2.7 billion connections per second performance

Design of an oximeter based on LED-LED configuration and FPGA technology

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Hardware Acceleration of Network Intrusion Detection System Using FPGA

This thesis presents new algorithms and hardware designs for Signature-based Network Intrusion Detection System (SB-NIDS) optimisation exploiting a hybrid hardwaresoftware co-designed embedded processing platform. The work describe concentrates on optimisation of a complete SB-NIDS Snort application software on a FPGA based hardware-software target rather than on the implementation of a single functional unit for hardware acceleration. Pattern Matching Hardware Accelerator (PMHA) based on Bloom filter was designed to optimise SB-NIDS performance for execution on a Xilinx MicroBlaze soft-core processor. The Bloom filter approach enables the potentially large number of network intrusion attack patterns to be efficiently represented and searched primarily using accesses to FPGA on-chip memory. The thesis demonstrates, the viability of hybrid hardware-software co-designed approach for SB-NIDS. Future work is required to investigate the effects of later generation FPGA technology and multi-core processors in order to clearly prove the benefits over conventional processor platforms for SB-NIDS. The strengths and weaknesses of the hardware accelerators and algorithms are analysed, and experimental results are examined to determine the effectiveness of the implementation. Experimental results confirm that the PMHA is capable of performing network packet analysis for gigabit rate network traffic. Experimental test results indicate that our SB-NIDS prototype implementation on relatively low clock rate embedded processing platform performance is approximately 1.7 times better than Snort executing on a general purpose processor on PC when comparing processor cycles rather than wall clock time

Using embedded hardware monitor cores in critical computer systems

The integration of FPGA devices in many different architectures and services makes monitoring and real time detection of errors an important concern in FPGA system design. A monitor is a tool, or a set of tools, that facilitate analytic measurements in observing a given system. The goal of these observations is usually the performance analysis and optimisation, or the surveillance of the system. However, System-on-Chip (SoC) based designs leave few points to attach external tools such as logic analysers. Thus, an embedded error detection core that allows observation of critical system nodes (such as processor cores and buses) should enforce the operation of the FPGA-based system, in order to prevent system failures. The core should not interfere with system performance and must ensure timely detection of errors. This thesis is an investigation onto how a robust hardware-monitoring module can be efficiently integrated in a target PCI board (with FPGA-based application processing features) which is part of a critical computing system. [Continues.

Revealing AES Encryption Device Key on 328P Microcontrollers with Differential Power Analysis

This research demonstrates the revealing of an advanced encryption standard (AES) encryption device key. The encryption device is applied to an ATMEGA328P microcontroller. The said microcontroller is a device commonly used in internet of things (IoT). We measured power consumption when the encryption process is taking place. The message sent to the encryption device is randomly generated, but the key used has a fixed value. The novelty of this research is the creation of a systematic and optimal circuit in carrying the differential power analysis or difference of means (DPA/DoM) technique, so the technique can be applied in key revealing on a microcontroller device by using 500 traces in 120 seconds

Land Cover Classification Implemented in FPGA

The main focus of the dissertation is Land Use/Land Cover Classification, implemented in FPGA, taking advantage of its parallelism, improving time between mathematical operations. The classifiers implemented will be Decision Tree and Minimum Distance reviewed in State of the Art Chapter. The results obtained pretend to contribute in fire prevention and fire combat, due to the information they extract about the fields where the implementation is applied to. The region of interest will Sado estuary, with future application to Mação, Santarém, inserted in FORESTER project, that had a lot of its area burnt in 2017 fires. Also, the data acquired from the implementation can help to update the previous land classification of the region. Image processing can be performed in a variety of platforms, such as CPU, GPU and FPGAs, with different advantages and disadvantages for each one. Image processing can be referred as massive data processing data in a visual context, due to its large amount of information per photo. Several studies had been made in accelerate classification techniques in hardware, but not so many have been applied in the same context of this dissertation. The outcome of this work shows the advantages of high data processing in hardware, in time and accuracy aspects. How the classifiers handle the region of study and can right classify it will be seen in this dissertation and the major advantages of accelerating some parts or the full classifier in hardware. The results of implementing the classifiers in hardware, done in the Zynq UltraScale+ MPSoC board, will be compared against the equivalent CPU implementation

Advanced photonic and electronic systems - WILGA 2017

WILGA annual symposium on advanced photonic and electronic systems has been organized by young scientist for young scientists since two decades. It traditionally gathers more than 350 young researchers and their tutors. Ph.D students and graduates present their recent achievements during well attended oral sessions. Wilga is a very good digest of Ph.D. works carried out at technical universities in electronics and photonics, as well as information sciences throughout Poland and some neighboring countries. Publishing patronage over Wilga keep Elektronika technical journal by SEP, IJET by PAN and Proceedings of SPIE. The latter world editorial series publishes annually more than 200 papers from Wilga. Wilga 2017 was the XL edition of this meeting. The following topical tracks were distinguished: photonics, electronics, information technologies and system research. The article is a digest of some chosen works presented during Wilga 2017 symposium. WILGA 2017 works were published in Proc. SPIE vol.10445

Design methodology addressing static/reconfigurable partitioning optimizing software defined radio (SDR) implementation through FPGA dynamic partial reconfiguration and rapid prototyping tools

The characteristics people request for communication devices become more and more demanding every day. And not only in those aspects dealing with communication speed, but also in such different characteristics as different communication standards compatibility, battery life, device size or price. Moreover, when this communication need is addressed by the industrial world, new characteristics such as reliability, robustness or time-to-market appear. In this context, Software Defined Radios (SDR) and evolutions such as Cognitive Radios or Intelligent Radios seem to be the technological answer that will satisfy all these requirements in a short and mid-term. Consequently, this PhD dissertation deals with the implementation of this type of communication system. Taking into account that there is no limitation neither in the implementation architecture nor in the target device, a novel framework for SDR implementation is proposed. This framework is made up of FPGAs, using dynamic partial reconfiguration, as target device and rapid prototyping tools as designing tool. Despite the benefits that this framework generates, there are also certain drawbacks that need to be analyzed and minimized to the extent possible. On this purpose, a SDR design methodology has been designed and tested. This methodology addresses the static/reconfigurable partitioning of the SDRs in order to optimize their implementation in the aforementioned framework. In order to verify the feasibility of both the design framework and the design methodology, several implementations have been carried out making use of them. A multi-standard modulator implementing WiFi, WiMAX and UMTS, a small-form-factor cognitive video transmission system and the implementation of several data coding functions over R3TOS, a hardware operating system developed by the University of Edinburgh, are these implementations.Las características que la gente exige a los dispositivos de comunicaciones son cada día más exigentes. Y no solo en los aspectos relacionados con la velocidad de comunicación, sino que también en diferentes características como la compatibilidad con diferentes estándares de comunicación, autonomía, tamaño o precio. Es más, cuando esta necesidad de comunicación se traslada al mundo industrial, aparecen nuevas características como fiabilidad, robustez o plazo de comercialización que también es necesario cubrir. En este contexto, las Radios Definidas por Software (SDR) y evoluciones como las Radios Cognitivas o Radios Inteligentes parecen la respuesta tecnológica que va a satisfacer estas necesidades a corto y medio plazo. Por ello, esta tesis doctoral aborda la implementación de este tipo de sistemas de comunicaciones. Teniendo en cuenta que no existe una limitación, ni en la arquitectura de implementación, ni en el tipo de dispositivo a usar, se propone un nuevo entrono de diseño formado por las FPGAs, haciendo uso de la reconfiguración parcial dinámica, y por las herramientas de prototipado rápido. A pesar de que este entorno de diseño ofrece varios beneficios, también genera algunos inconvenientes que es necesario analizar y minimizar en la medida de lo posible. Con este objetivo, se ha diseñado y verificado una metodología de diseño de SDRs. Esta metodología se encarga del particionado estático/reconfigurable de las SDRs para optimizar su implementación sobre el entrono de diseño antes comentado. Para verificar la viabilidad tanto del entorno, como de la metodología de diseño propuesta, se han realizado varias implementaciones que hacen uso de ambas cosas. Estas implementaciones son: un modulador multi-estándar que implementa WiFi, WiMAX y UMTS, un sistema cognitivo y compacto de transmisión de video y la implementación de varias funciones de codificación de datos sobre R3TOS, un sistema operativo hardware desarrollado por la Universidad de Edimburgo