A Neural Model of How the Brain Computes Heading from Optic Flow in Realistic Scenes

Animals avoid obstacles and approach goals in novel cluttered environments using visual information, notably optic flow, to compute heading, or direction of travel, with respect to objects in the environment. We present a neural model of how heading is computed that describes interactions among neurons in several visual areas of the primate magnocellular pathway, from retina through V1, MT+, and MSTd. The model produces outputs which are qualitatively and quantitatively similar to human heading estimation data in response to complex natural scenes. The model estimates heading to within 1.5° in random dot or photo-realistically rendered scenes and within 3° in video streams from driving in real-world environments. Simulated rotations of less than 1 degree per second do not affect model performance, but faster simulated rotation rates deteriorate performance, as in humans. The model is part of a larger navigational system that identifies and tracks objects while navigating in cluttered environments.National Science Foundation (SBE-0354378, BCS-0235398); Office of Naval Research (N00014-01-1-0624); National-Geospatial Intelligence Agency (NMA201-01-1-2016

Modeling and Simulation of Nonlinearly Loaded Electromagnetic Systems via Reduced Order Models - A Case Study: Energy Selective Surfaces

L'abstract è presente nell'allegato / the abstract is in the attachmen

Modelação comportamental e pré-distorção digital de transmissores de rádio-frequência

Doutoramento em Engenharia ElectrotécnicaNos atuais sistemas de telecomunicações, os transmissores de rádio-frequência são desenvolvidos tendo maioritariamente em conta a eficiência da conversão da potência fornecida da fonte em potência de rádio-frequência. Este tipo de desenho resulta em amplificadores de potência com características de transmissão não-lineares, que distorcem severamente o envelope de informação no processo de amplificação, gerando distorção fora da banda. Para corrigir este problema utiliza-se um processo de compensação não linear, sendo que a pré-distorção digital se tem favorecido pela sua flexibilidade e precisão. Este método é tipicamente aplicado de uma forma cega, por força bruta até se obter a compensação desejada. No entanto, quando o método se mostra ineficaz, como se verificou em amplificadores de potência baseados em transístores de nitreto de gálio, é difícil saber o que modificar nos sistemas para os tornar de novo úteis. De forma a compreender e desenhar sistemas de pré-distorção digital robustos é necessário, por um lado, perceber o comportamento dos amplificadores de rádio-frequência, por outro, perceber as limitações e relações entre os modelos digitais e o comportamento real do amplificador. Nesse sentido, esta tese explora e descreve estas relações de forma a suportar a escolha de modelos de pré-distorção, desenvolve novos modelos baseados no comportamento dos transístores, e propõe métodos de caracterização para os amplificadores de RF.In current telecommunication systems, the main concern when developing the radio frequency transmitter is power efficiency. This type of design generally leads to a highly nonlinear transmission characteristic, mainly due to the radio frequency power amplifier. This nonlinear transmission severely distorts the information envelope, leading to spectral regrowth, out-of-band distortion. To correct this problem a nonlinear compensation process is employed. For this application, digital predistortion is generally favored for its flexibility and accuracy. Digital predistortion is mostly applied in a blind manner, using brute force until the desired compensation is achieved. Because of this, when the method fails, as it has in gallium nitride based power amplifiers, it is difficult to modify the system to achieve the desired results. To understand and design robust predistortion systems, it is both necessary to have knowledge of the power amplifiers’ behavior, on one hand, and understand the limitations and relations between the digital models and these behaviors, on the other. To do this, this thesis explores and describes these relationships, granting support to the digital predistortion model choice, it further develops new predistortion models based on the physics of the transistors’ behaviors, and it proposes methods for the characterization of radio frequency power amplifiers

ワイヤレス通信のための先進的な信号処理技術を用いた非線形補償法の研究

The inherit nonlinearity in analogue front-ends of transmitters and receivers have had primary impact on the overall performance of the wireless communication systems, as it gives arise of substantial distortion when transmitting and processing signals with such circuits. Therefore, the nonlinear compensation (linearization) techniques become essential to suppress the distortion to an acceptable extent in order to ensure sufficient low bit error rate. Furthermore, the increasing demands on higher data rate and ubiquitous interoperability between various multi-coverage protocols are two of the most important features of the contemporary communication system. The former demand pushes the communication system to use wider bandwidth and the latter one brings up severe coexistence problems. Having fully considered the problems raised above, the work in this Ph.D. thesis carries out extensive researches on the nonlinear compensations utilizing advanced digital signal processing techniques. The motivation behind this is to push more processing tasks to the digital domain, as it can potentially cut down the bill of materials (BOM) costs paid for the off-chip devices and reduce practical implementation difficulties. The work here is carried out using three approaches: numerical analysis & computer simulations; experimental tests using commercial instruments; actual implementation with FPGA. The primary contributions for this thesis are summarized as the following three points: 1) An adaptive digital predistortion (DPD) with fast convergence rate and low complexity for multi-carrier GSM system is presented. Albeit a legacy system, the GSM, however, has a very strict requirement on the out-of-band emission, thus it represents a much more difficult hurdle for DPD application. It is successfully implemented in an FPGA without using any other auxiliary processor. A simplified multiplier-free NLMS algorithm, especially suitable for FPGA implementation, for fast adapting the LUT is proposed. Many design methodologies and practical implementation issues are discussed in details. Experimental results have shown that the DPD performed robustly when it is involved in the multichannel transmitter. 2) The next generation system (5G) will unquestionably use wider bandwidth to support higher throughput, which poses stringent needs for using high-speed data converters. Herein the analog-to-digital converter (ADC) tends to be the most expensive single device in the whole transmitter/receiver systems. Therefore, conventional DPD utilizing high-speed ADC becomes unaffordable, especially for small base stations (micro, pico and femto). A digital predistortion technique utilizing spectral extrapolation is proposed in this thesis, wherein with band-limited feedback signal, the requirement on ADC speed can be significantly released. Experimental results have validated the feasibility of the proposed technique for coping with band-limited feedback signal. It has been shown that adequate linearization performance can be achieved even if the acquisition bandwidth is less than the original signal bandwidth. The experimental results obtained by using LTE-Advanced signal of 320 MHz bandwidth are quite satisfactory, and to the authors’ knowledge, this is the first high-performance wideband DPD ever been reported. 3) To address the predicament that mobile operators do not have enough contiguous usable bandwidth, carrier aggregation (CA) technique is developed and imported into 4G LTE-Advanced. This pushes the utilization of concurrent dual-band transmitter/receiver, which reduces the hardware expense by using a single front-end. Compensation techniques for the respective concurrent dual-band transmitter and receiver front-ends are proposed to combat the inter-band modulation distortion, and simultaneously reduce the distortion for the both lower-side band and upper-side band signals.電気通信大学201

Bandlimited Digital Predistortion of Wideband RF Power Amplifiers

The increase in the demand for high data rates has led to the deployment of wider bandwidths and complex waveforms in wireless communication systems. Multicarrier waveforms such as orthogonal frequency division multiplexing (OFDM) employed in modern systems are very sensitive to the transmitter chain nonidealities due to their high peak-to-average-power-ratio (PAPR) characteristic. They are therefore affected by nonlinear transmitter components particularly the power amplifier (PA). Moreover, to enhance power efficiency, PAs typically operate near saturation region and hence become more nonlinear. Power efficiency is highly desirable especially in battery powered and portable devices as well as in base stations. Hence there is a clear need for efficient linearization algorthms which improve power efficiency while maintaining high spectral efficiency. Digital predistortion (DPD) has been recognized as one of the most effective methods in mitigating PA nonlinear distortions. The method involves the application of inverse PA nonlinear function upstream of the PA such that the overall system output has a linear amplification. The computation of the nonlinearity profile and the inversion of the PA function are particularly difficult and complicated especially when involving wideband radio access waveforms, and therefore memory effects, which are being employed in modern communication systems, such as in Long Term Evolution/Advanced (LTE/LTE-A). In the recent technical literature, different approaches which focus on the linearization of specific frequency bands or sub-bands only have been developed to alleviate this problem, thereby reducing the complexity of DPD. In this thesis, we focus on the development and characterization of a bandlimited DPD solution specifically tailored towards the linearization at and around the main carrier(s) in single carrier deployment or contiguous carrier aggregation of two or more component carriers. In terms of parameter identification, the solution is based on the reduced-complexity closed-loop decorrelation-based parameter learning principle, which is also able to track time-varying changes in the transmitter components adaptively. The proposed bandlimited solution is designed to linearize the inband and out-of-band (OOB) distortions in the immediate vicinity of the main carrier(s) while assuming the distortions more far away in the spectrum are suppressed by transmit or duplex filters. This is implemented using FIR filters to limit the bandwidth expansion during basis functions generation and to restrain the bandwidth of the feedback observation signal, thus reducing the DPD sample rates in both the main path processing and the parameter learning. The performance of the proposed bandlimited DPD solution is evaluated using comprehensive simulations involving memoryless and memory-based PA models, as well as true RF measurements using commercial LTE-A base station and mobile device PAs. The achieved results validate and demonstrate efficient suppression of inband and OOB distortions in real-world application scenarios. Furthermore, the bandlimited DPD consistently outperforms the conventional DPD solutions in the memory-based PA model and practical PA scenarios in suppressing the OOB distortion in the immediate vicinity of the main carrier(s) by approximately 1 - 2 dB. The results provide sufficient grounds for the application of the bandlimited DPD solution in the classical single carrier deployment or in contiguous carrier aggregation of two or more component carriers where conventional DPD solutions would otherwise be highly complex

Characterization and Emulation of Low-Voltage Power Line Channels for Narrowband and Broadband Communication

The demand for smart grid and smart home applications has raised the recent interest in power line communication (PLC) technologies, and has driven a broad set of deep surveys in low-voltage (LV) power line channels. This book proposes a set of novel approaches, to characterize and to emulate LV power line channels in the frequency range from0.15to 10 MHz, which closes gaps between the traditional narrowband (up to 500 kHz) and broadband (above1.8 MHz) ranges

Characterization and Emulation of Low-Voltage Power Line Channels for Narrowband and Broadband Communication

The demand for smart grid and smart home applications has raised the recent interest in power line communication (PLC) technologies, and has driven a broad set of deep surveys in low-voltage (LV) power line channels. This book proposes a set of novel approaches, to characterize and to emulate LV power line channels in the frequency range from0.15to 10 MHz, which closes gaps between the traditional narrowband (up to 500 kHz) and broadband (above1.8 MHz) ranges

Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain

Magnetoencephalography (MEG) is a noninvasive technique for investigating neuronal activity in the living human brain. The time resolution of the method is better than 1 ms and the spatial discrimination is, under favorable circumstances, 2-3 mm for sources in the cerebral cortex. In MEG studies, the weak 10 fT-1 pT magnetic fields produced by electric currents flowing in neurons are measured with multichannel SQUID (superconducting quantum interference device) gradiometers. The sites in the cerebral cortex that are activated by a stimulus can be found from the detected magnetic-field distribution, provided that appropriate assumptions about the source render the solution of the inverse problem unique. Many interesting properties of the working human brain can be studied, including spontaneous activity and signal processing following external stimuli. For clinical purposes, determination of the locations of epileptic foci is of interest. The authors begin with a general introduction and a short discussion of the neural basis of MEG. The mathematical theory of the method is then explained in detail, followed by a thorough description of MEG instrumentation, data analysis, and practical construction of multi-SQUID devices. Finally, several MEG experiments performed in the authors' laboratory are described, covering studies of evoked responses and of spontaneous activity in both healthy and diseased brains. Many MEG studies by other groups are discussed briefly as well.Peer reviewe

Spatiotemporal techniques in multimodal imaging for brain mapping and epilepsy

Thesis (Ph.D.)--Boston UniversityThis thesis explored multimodal brain imaging using advanced spatiotemporal techniques. The first set of experiments were based on simulations. Much controversy exists in the literature regarding the differences between magnetoencephalography (MEG) and electroencephalography (EEG}, both practically and theoretically. The differences were explored using simulations that evaluated the expected signal-to-noise ratios from reasonable brain sources. MEG and EEG were found to be complementary, with each modality optimally suited to image activity from different areas of the cortical surface. Consequently, evaluations of epileptic patients and general neuroscience experiments will both benefit from simultaneously collected MEG/EEG. The second set of experiments represent an example of MEG combined with magnetic resonance imaging (MRI) and functional MRI (fMRI) applied to healthy subjects. The study set out to resolve two questions relating to shape perception. First, does the brain activate functional areas sequentially during shape perception, as has been suggested in recent literature? Second, which , if any, functional areas are active time-locked with reaction-time? The study found that functional areas are non-sequentially activated, and that area IT is active time-locked with reaction-time. These two points, coupled with the method for multimodal integration , can help further develop our understanding of shape perception in particular, and cortical dynamics in general for healthy subjects. Broadly, these two studies represent practical guidelines for epilepsy evaluations and brain mapping studies. For epilepsy studies, clinicians could combine MEG and EEG to maximize the probability of finding the source of seizures. For brain mapping in general, EEG, MEG, MRI and fMRI can be combined in the methods outlined here to obtain more sophisticated views of cortical dynamics