Signal and power integrity co-simulation using the multi-layer finite difference method

Mixed signal system-on-package (SoP) technology is a key enabler for increasing functional integration, especially in mobile and wireless systems. Due to the presence of multiple dissimilar modules, each having unique power supply requirements, the design of the power distribution network (PDN) becomes critical. Typically, this PDN is designed as alternating layers of power and ground planes with signal interconnects routed in between or on top of the planes. The goal for the simulation of multi-layer power/ground planes, is the following: Given a stack-up and other geometrical information, it is required to find the network parameters (S/Y/Z) between port locations. Commercial packages have extremely complicated stack-ups, and the trend to increasing integration at the package level only points to increasing complexity. It is computationally intractable to solve these problems using these existing methods. The approach proposed in this thesis for obtaining the response of the PDN is the multi-layer finite difference method (M-FDM). A surface mesh / finite difference based approach is developed, which leads to a system matrix that is sparse and banded, and can be solved efficiently. The contributions of this research are the following: 1. The development of a PDN modeler for multi-layer packages and boards called the the multi-layer finite difference method. 2. The enhancement of M-FDM using multi-port connection networks to include the effect of fringe fields and gap coupling. 3. An adaptive triangular mesh based scheme called the multi-layer finite element method (MFEM) to address the limitations of M-FDM 4. The use of modal decomposition for the co-simulation of signal nets with the PDN. 5. The use of a robust GA-based optimizer for the selection and placement of decoupling capacitors in multi-layer geometries. 6. Implementation of these methods in a tool called MSDT 1.Ph.D.Committee Chair: Madhavan Swaminathan; Committee Member: Andrew F. Peterson; Committee Member: David C. Keezer; Committee Member: Saibal Mukhopadyay; Committee Member: Suresh Sitarama

Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression

A Unified Cognitive Model of Visual Filling-In Based on an Emergic Network Architecture

The Emergic Cognitive Model (ECM) is a unified computational model of visual filling-in based on the Emergic Network architecture. The Emergic Network was designed to help realize systems undergoing continuous change. In this thesis, eight different filling-in phenomena are demonstrated under a regime of continuous eye movement (and under static eye conditions as well). ECM indirectly demonstrates the power of unification inherent with Emergic Networks when cognition is decomposed according to finer-grained functions supporting change. These can interact to raise additional emergent behaviours via cognitive re-use, hence the Emergic prefix throughout. Nevertheless, the model is robust and parameter free. Differential re-use occurs in the nature of model interaction with a particular testing paradigm. ECM has a novel decomposition due to the requirements of handling motion and of supporting unified modelling via finer functional grains. The breadth of phenomenal behaviour covered is largely to lend credence to our novel decomposition. The Emergic Network architecture is a hybrid between classical connectionism and classical computationalism that facilitates the construction of unified cognitive models. It helps cutting up of functionalism into finer-grains distributed over space (by harnessing massive recurrence) and over time (by harnessing continuous change), yet simplifies by using standard computer code to focus on the interaction of information flows. Thus while the structure of the network looks neurocentric, the dynamics are best understood in flowcentric terms. Surprisingly, dynamic system analysis (as usually understood) is not involved. An Emergic Network is engineered much like straightforward software or hardware systems that deal with continuously varying inputs. Ultimately, this thesis addresses the problem of reduction and induction over complex systems, and the Emergic Network architecture is merely a tool to assist in this epistemic endeavour. ECM is strictly a sensory model and apart from perception, yet it is informed by phenomenology. It addresses the attribution problem of how much of a phenomenon is best explained at a sensory level of analysis, rather than at a perceptual one. As the causal information flows are stable under eye movement, we hypothesize that they are the locus of consciousness, howsoever it is ultimately realized

Radar Technology

In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design

Earth imaging with microsatellites: An investigation, design, implementation and in-orbit demonstration of electronic imaging systems for earth observation on-board low-cost microsatellites.

This research programme has studied the possibilities and difficulties of using 50 kg microsatellites to perform remote imaging of the Earth. The design constraints of these missions are quite different to those encountered in larger, conventional spacecraft. While the main attractions of microsatellites are low cost and fast response times, they present the following key limitations: Payload mass under 5 kg, Continuous payload power under 5 Watts, peak power up to 15 Watts, Narrow communications bandwidths (9.6 / 38.4 kbps), Attitude control to within 5°, No moving mechanics. The most significant factor is the limited attitude stability. Without sub-degree attitude control, conventional scanning imaging systems cannot preserve scene geometry, and are therefore poorly suited to current microsatellite capabilities. The foremost conclusion of this thesis is that electronic cameras, which capture entire scenes in a single operation, must be used to overcome the effects of the satellite's motion. The potential applications of electronic cameras, including microsatellite remote sensing, have erupted with the recent availability of high sensitivity field-array CCD (charge-coupled device) image sensors. The research programme has established suitable techniques and architectures necessary for CCD sensors, cameras and entire imaging systems to fulfil scientific/commercial remote sensing despite the difficult conditions on microsatellites. The author has refined these theories by designing, building and exploiting in-orbit five generations of electronic cameras. The major objective of meteorological scale imaging was conclusively demonstrated by the Earth imaging camera flown on the UoSAT-5 spacecraft in 1991. Improved cameras have since been carried by the KITSAT-1 (1992) and PoSAT-1 (1993) microsatellites. PoSAT-1 also flies a medium resolution camera (200 metres) which (despite complete success) has highlighted certain limitations of microsatellites for high resolution remote sensing. A reworked, and extensively modularised, design has been developed for the four camera systems deployed on the FASat-Alfa mission (1995). Based on the success of these missions, this thesis presents many recommendations for the design of microsatellite imaging systems. The novelty of this research programme has been the principle of designing practical camera systems to fit on an existing, highly restrictive, satellite platform, rather than conceiving a fictitious small satellite to support a high performance scanning imager. This pragmatic approach has resulted in the first incontestable demonstrations of the feasibility of remote sensing of the Earth from inexpensive microsatellites

Optical signal processing for efficient information networks

With the internet and rise of personal electronics there is an ever increasing amount of data collected and transmitted every day; modern communication systems will soon be overwhelmed. The driving force behind the demand is an increasing speed of signal acquisition, in the public domain, as well as medicine and industry; newer technologies allow massive amounts of data produced through text, voice, and video. This puts strain on both signal acquisition systems and communications systems to increase the total information flow. Transmission down fiber links is enabled by the large but limited bandwidth of optical fiber, and as we look toward the future, efficient use of the available optical bandwidth is paramount. I apply the large bandwidth of fiber and ultrafast speed of nonlinear optics to solve these problems, implementing high-speed and efficient signal acquisition and communication systems. With the increased volume of information being transferred, compression of data has become essential to allow multimedia communication. Data is acquired then compressed and transmitted, requiring massive computing power. Using the information theory technique coined “compressed sensing”, we demonstrate real time compression at signal acquisition, removing a timeconsuming and bandwidth inefficient step in a complete communication link. I use dispersion and nonlinear wave mixing in optical fiber, and gigahertz electro-optics to shape light at terahertz speeds, reaching towards the limit of compressed image acquisition. To complete a high-speed communications link, I investigate the use of Nyquist optical time division multiplexing to maximize spectral efficiency. The square spectral shape of a Nyquist pulse is ideal, but the pulse ripples on forever in the time domain, presenting problems for demultiplexing Nyquist signals at the receiver. I present a solution using coherent detection with a biorthogonal Nyquist pulse to eliminate interference from neighboring channels, and implement a proof of concept system using nonlinear wave mixing. Stable clock transfer is essential for coherent communication, but environmental fluctuations erode clock information, reducing the effective data rate of the communications channel. I present a versatile solution for stable time and frequency transfer using dispersion and nonlinear wave mixing in optical fiber

Translational pipelines for closed-loop neuromodulation

Closed-loop neuromodulation systems have shown significant potential for addressing unmet needs in the treatment of disorders of the central nervous system, yet progress towards clinical adoption has been slow. Advanced technological developments often stall in the preclinical stage by failing to account for the constraints of implantable medical devices, and due to the lack of research platforms with a translational focus. This thesis presents the development of three clinically relevant research systems focusing on refinements of deep brain stimulation therapies. First, we introduce a system for synchronising implanted and external stimulation devices, allowing for research into multi-site stimulation paradigms, cross-region neural plasticity, and questions of phase coupling. The proposed design aims to sidestep the limited communication capabilities of existing commercial implant systems in providing a stimulation state readout without reliance on telemetry, creating a cross-platform research tool. Next, we present work on the Picostim-DyNeuMo adaptive neuromodulation platform, focusing on expanding device capabilities from activity and circadian adaptation to bioelectric marker--based responsive stimulation. Here, we introduce a computationally optimised implementation of a popular band power--estimation algorithm suitable for deployment in the DyNeuMo system. The new algorithmic capability was externally validated to establish neural state classification performance in two widely-researched use cases: Parkinsonian beta bursts and seizures. For in vivo validation, a pilot experiment is presented demonstrating responsive neurostimulation to cortical alpha-band activity in a non-human primate model for the modulation of attention state. Finally, we turn our focus to the validation of a recently developed method to provide computationally efficient real-time phase estimation. Following theoretical analysis, the method is integrated into the commonly used Intan electrophysiological recording platform, creating a novel closed-loop optogenetics research platform. The performance of the research system is characterised through a pilot experiment, targeting the modulation of cortical theta-band activity in a transgenic mouse model

Deep learning for internet of underwater things and ocean data analytics

The Internet of Underwater Things (IoUT) is an emerging technological ecosystem developed for connecting objects in maritime and underwater environments. IoUT technologies are empowered by an extreme number of deployed sensors and actuators. In this thesis, multiple IoUT sensory data are augmented with machine intelligence for forecasting purposes