Norm Optimal Iterative Learning Control with Application to Problems in Accelerator based Free Electron Lasers and Rehabilitation Robotics

This paper gives an overview of the theoretical basis of the norm optimal approach to iterative learning control followed by results that describe more recent work which has experimentally benchmarking the performance that can be achieved. The remainder of then paper then describes its actual application to a physical process and a very novel application in stroke rehabilitation

On Translator's Cultural Orientation - A Comparative Study of the Translation of Hong Lou Meng

In recent decades, transient faults have become a critical issue in modernelectronic devices. Therefore, many fault-tolerant techniques have been proposedto increase system reliability, such as active redundancy, which can beimplemented in both space and time dimensions. The main challenge of activeredundancy is to introduce the minimal overhead of redundancy and to schedulethe tasks. In many pervious works, perfect fault detectors are assumed to simplifythe problem. However, the induced resource and time overheads of suchfault detectors make them impractical to be implemented. In order to tacklethe problem, an alternative approach was proposed based on imperfect faultdetectors. So far, only software implementation is studied for the proposed imperfectfault detection approach. In this thesis, we take hardware-acceleration intoconsideration. Field-programmable gate array (FPGA) is used to accommodatetasks in hardware. In order to utilize the FPGA resources efficiently, themapping and the selection of fault detectors for each task replica have to be carefullydecided. In this work, we present two optimization approaches consideringtwo FPGA technologies, namely, statically reconfigurable FPGA and dynamicallyreconfigurable FPGA respectively. Both approaches are evaluated andcompared with the proposed software-only approach by extensive experiments

An Intelligent Architecture Based on Field Programmable Gate Arrays Designed to Detect Moving Objects by Using Principal Component Analysis

This paper presents a complete implementation of the Principal Component Analysis (PCA) algorithm in Field Programmable Gate Array (FPGA) devices applied to high rate background segmentation of images. The classical sequential execution of different parts of the PCA algorithm has been parallelized. This parallelization has led to the specific development and implementation in hardware of the different stages of PCA, such as computation of the correlation matrix, matrix diagonalization using the Jacobi method and subspace projections of images. On the application side, the paper presents a motion detection algorithm, also entirely implemented on the FPGA, and based on the developed PCA core. This consists of dynamically thresholding the differences between the input image and the one obtained by expressing the input image using the PCA linear subspace previously obtained as a background model. The proposal achieves a high ratio of processed images (up to 120 frames per second) and high quality segmentation results, with a completely embedded and reliable hardware architecture based on commercial CMOS sensors and FPGA devices

On Design and Implementation of Generic Fuzzy Logic Controllers

Soft computing techniques, unlike traditional deterministic logic based computing techniques, sometimes also called as hard computing, are tolerant of imprecision, uncertainty, and approximation. The primary inspiration for soft computing is the human mind and its ability to address day-to-day problems. The primary constituents of soft computing techniques are Artificial Neural Network, Fuzzy Logic Systems, and Evolutionary Computing. This thesis presents design and implementation of a generic hardware architecture based Type-IMamdani fuzzy logic controller (FLC) implemented on a programmable device, which can be remotely configured in real-time over Ethernet. This reconfigurability is added as a feature to existing FLCs in literature. It enables users to change parameters (those drive the FLC systems) in real-time and eliminate repeated hardware programming whenever there is a need. Realization of these systems in real-time is difficult as the computational complexity increases exponentially with an increase in the number of inputs. Hence challenge lies in reducing the Rulebase significantly such that the inference time and the throughput time is perceivable for real-time applications. To achieve these objectives, a modified thresholded fired rules hypercube (MT-FRHC) algorithm for Rulebase reduction is proposed and implemented. MT-FRHC reduces the useful rules without compromising system accuracy and improves the cycle time in terms of fuzzy logic operations per second (FzLOPS). It is imperative to understand that there are over sixty reconfigurable parameters, and it becomes an arduous task for a user to manage them. Therefore, a genetic algorithm based parameter extraction technique is proposed. This will help to develop a course tuning and provide default parameters that can be later fine-tuned by the users remotely through the Web-based User Interface. A hardware software codesign architecture for FLC is developed on TI C6748 DSP hardware with Sys/BIOS RTOS and seamlessly integrated with a webbased user interface (WebUI) for reconfigurability. Fuzzy systems employ defuzzifier to convert the fuzzy output into the real world crisp output. Centroid of Area (CoA) method is most widely used defuzzification method for control applications. However, the prevalent method of CoA computation is based on the principle of Riemann sum which is computationally complex. A vertices based CoA (VBCoA) defuzzification method is introduced. It has been observed that the proposed VBCoA method for COA computation is faster than the Riemann sum based CoA computation. A code optimization technique, exclusive to TI DSPs, is implemented to achieve memory and machine cycle optimization. The WebUI is developed in accordance to a client–server model using ASP.NET. It acquires fuzzy parameters from users, and a server application is dedicated to handling data communication between the hardware and the server. Testing and analysis of this hardware G-FLCS has been carried out by using hardware-in-loop test to control various system models in Simulink environment which includes water level control in a two tank system, intelligent cruise control system, speed control of an armature controlled DC motor and anti-windup control. The performance of the proposed G-FLCS is compared to Fuzzy Inference System of Matlab Fuzzy Logic Toolbox and PID controller in terms of settling time, transient time and steady state error. This proposed MT-FRHC based G-FLCS with VBCoA defuzzification implemented on C6748 DSP was finally deployed to control the radial position of plasma in Aditya Tokamak fusion reactor. The proposed G-FLCS is observed to deliver a smooth and fast system response

Reduced Switching Connectivity for Large Scale Antenna Selection

In this paper, we explore reduced-connectivity radio frequency (RF) switching networks for reducing the analog hardware complexity and switching power losses in antenna selection (AS) systems. In particular, we analyze different hardware architectures for implementing the RF switching matrices required in AS designs with a reduced number of RF chains. We explicitly show that fully-flexible switching matrices, which facilitate the selection of any possible subset of antennas and attain the maximum theoretical sum rates of AS, present numerous drawbacks such as the introduction of significant insertion losses, particularly pronounced in massive multiple-input multiple-output (MIMO) systems. Since these disadvantages make fully-flexible switching suboptimal in the energy efficiency sense, we further consider partially-connected switching networks as an alternative switching architecture with reduced hardware complexity, which we characterize in this work. In this context, we also analyze the impact of reduced switching connectivity on the analog hardware and digital signal processing of AS schemes that rely on channel power information. Overall, the analytical and simulation results shown in this paper demonstrate that partially-connected switching maximizes the energy efficiency of massive MIMO systems for a reduced number of RF chains, while fully-flexible switching offers sub-optimal energy efficiency benefits due to its significant switching power losses.Comment: 14 pages, 11 figure

Evaluating Performance and Efficiency of a 16-bit Substitution Box on an FPGA

A Substitution Box (S-Box) is an integral component of modern block ciphers that provides confusion. The term confusion was introduced by Shannon in 1949 and it refers to the complexity of the relationship between the key and the ciphertext. Most S-Boxes are non-linear in order to promote confusion. Due to this, the S-Box is usually the most complex component of a block cipher. The Advanced Encryption Standard (AES) features an 8-bit S-Box where the output depends on the Galois field multiplicative inverse of the input. MK-3 is a sponge based Authenticated Encryption (AE) algorithm which provides both authenticity and confidentiality. It was developed through a joint effort between the Rochester Institute of Technology and the former Harris Corporation, now L3Harris. The MK-3 algorithm has a state that is 512 bits wide and it uses 32 instances of a 16-bit S-Box to cover the entire state. These 16-bit S-Boxes are similar to what is seen in the AES, however, they are notably larger and more complex. Binary Galois field arithmetic is well suited to hardware implementations where addition and multiplication are mapped to a combination of basic XOR and AND operations. A simple method to calculate Galois field multiplicative inversion is through the extended Euclidean algorithm. This is, however, very expensive to implement in hardware. A possible solution is to use a composite field representation, where the original operation is broken down to a series of simpler operations in the base field. This lends itself very well to implementations that consume less area and power with better performance. Given the size and number of the S-Boxes in MK-3, these units contribute to the majority of the implementation resources. Several composite field structures are explored in this work which provide different area utilization and clock frequency characteristics. This thesis evaluates the composite field structures and recommends several candidates for high performing MK-3 Field Programmable Gate Array (FPGA) applications

A neural network for mining large volumes of time series data

Efficiently mining large volumes of time series data is amongst the most challenging problems that are fundamental in many fields such as industrial process monitoring, medical data analysis and business forecasting. This paper discusses a high-performance neural network for mining large time series data set and some practical issues on time series data mining. Examples of how this technology is used to search the engine data within a major UK eScience Grid project (DAME) for supporting the maintenance of Rolls-Royce aero-engine are presented

VLSI Implementation of LDPC Codes

Coded modulation is a bandwidth-efficient scheme that integrates channel coding and modulation into one single entity to improve performance with the same spectral efficiency compared to uncoded modulation. Low-density parity-check (LDPC) codes are the most powerful error correction codes (ECCs) and approach the Shannon limit, while having a relatively low decoding complexity. Therefore, the idea of combining LDPC codes and bandwidth-efficient modulation has been widely considered. In this thesis we will consider LDPC codes as an Error Correcting Code and study it’s performance with BPSK system in AWGN environment and study different kind of characteristics of the system. LDPC system consists of two parts Encoder and Decoder. LDPC encoder encodes the data and sends it to the channel. The LDPC encoding performance depends on Parity matrix behavior which has characteristics like Rate, Girth, Size and Regularity. We will study the performance characteristics according to these characteristics and find performance variation in term of SNR performance. The decoder receives the data from the channel and decodes it. LDPC decoder has characteristics like time of iteration in addition all parity check matrix characteristics. We will also study the performance according to these characteristics. The main objective of this thesis is to implement LDPC system in FPGA. LDPC Encoder is implementation is done using Shift-Register based design to reduce complexity. LDPC decoder is used to decode the information received from the channel and decode the message to find the information. In the decoder we have used Modified Sum Product (MSP) Algorithm to decode, In the MSP we have used some quantized values to decode the data using Look Up Table (LUT) approximation. Finally we compare the SNR performance of theoretical LDPC system’s with FPGA implemented LDPC system’s performance