Deep Learning for Audio Signal Processing

Given the recent surge in developments of deep learning, this article provides a review of the state-of-the-art deep learning techniques for audio signal processing. Speech, music, and environmental sound processing are considered side-by-side, in order to point out similarities and differences between the domains, highlighting general methods, problems, key references, and potential for cross-fertilization between areas. The dominant feature representations (in particular, log-mel spectra and raw waveform) and deep learning models are reviewed, including convolutional neural networks, variants of the long short-term memory architecture, as well as more audio-specific neural network models. Subsequently, prominent deep learning application areas are covered, i.e. audio recognition (automatic speech recognition, music information retrieval, environmental sound detection, localization and tracking) and synthesis and transformation (source separation, audio enhancement, generative models for speech, sound, and music synthesis). Finally, key issues and future questions regarding deep learning applied to audio signal processing are identified.Comment: 15 pages, 2 pdf figure

A Vector Channel Based Approach to MIMO Radar Waveform Design for Extended Targets

Radar systems have been used for many years for estimating, detecting, classifying, and imaging objects of interest (targets). Stealthier targets and more cluttered environments have created a need for more sophisticated radar systems to gain more precise information about the radar environment. Because modern radar systems are largely defined in software, adaptive radar systems have emerged that tailor system parameters such as the transmitted waveform and receiver filter to the target and environment in order to address this need. The basic structure of a radar system exhibits many similarities to the structure of a communication system. Recognizing the parallel composition of radar systems and information transmission systems, initial works have begun to explore the application of information theory to radar system design, but a great deal of work still remains to make a full and clear connection between the problems addressed by radar systems and communication systems. Forming a comprehensive definition of this connection between radar systems and information transmission systems and associated problem descriptions could facilitate the cross-discipline transfer of ideas and accelerate the development and improvement of new system design solutions in both fields. In particular, adaptive radar system design is a relatively new field which stands to benefit from the maturity of information theory developed for information transmission if a parallel can be drawn to clearly relate similar radar and communication problems. No known previous work has yet drawn a clear parallel between the general multiple-input multiple-output (MIMO) radar system model considering both the detection and estimation of multiple extended targets and a similar multiuser vector channel information transmission system model. The goal of this dissertation is to develop a novel vector channel framework to describe a MIMO radar system and to study information theoretic adaptive radar waveform design for detection and estimation of multiple radar targets within this framework. Specifically, this dissertation first provides a new compact vector channel model for representing a MIMO radar system which illustrates the parallel composition of radar systems and information transmission systems. Second, using the proposed framework this dissertation contributes a compressed sensing based information theoretic approach to waveform design for the detection of multiple extended targets in noiseless and noisy scenarios. Third, this dissertation defines the multiple extended target estimation problem within the framework and proposes a greedy signal to interference-plus-noise ratio (SINR) maximizing procedure based on a similar approach developed for a collaborative multibase wireless communication system to optimally design wave forms in this scenario

Applications in Low-Power Phased Array Weather Radars

Low-cost X-band radars are an emerging technology that offer significant advantages over traditional systems for weather remote sensing applications. X-band radars provide enhanced angular resolution at a fraction of the aperture size compared to larger, lower frequency systems. Because of their low cost and small form factor, these radars can now be integrated into more research and commercial applications. This work presents research and development activities using a low-cost, X-band (9410 MHz) Phase-Tilt Radar. The phase-tilt design is a novel phased array architecture that allows for rapid electronic scanning in azimuth and mechanical tilting in elevation, as a compromise between cost and performance. This work focuses on field studies and experiments in three meteorological applications. The first stage of research focuses on the real-world application of phased array radars in forest fire monitoring and observation. From April to May 2013, a phase-tilt radar was deployed to South Australia and underwent a field campaign to make polarimetric observations of prescribed burns within and around the Adelaide Hills region. Measurements show the real-time evolution of the smoke plume dynamics at a spatial and temporal resolution that has never before been observed with an X-band radar. This dissertation will perform data analysis on results from this field campaign. Results are compared against existing work, theories, and approaches. In the second stage of research, field experiments are performed to assess the data quality of X-band phased array radars. Specifically, this research focuses on the measurement of and techniques to improve the variance of weather product estimators for dual-polarized systems. Variability in the radar products is a complicated relationship between the radar system specifications, scanning strategy, and the physics governing precipitation. Here, the variance of the radar product estimators is measured using standard radar scanning strategies employed in traditional mechanical antenna systems. Results are compared against adaptive scan strategies such as beam multiplexing and frequency diversity. This work investigates the improvement that complex scanning strategies offer in dual-polarized, X-band phased array radar systems. In the third stage of research, simulations and field experiments are conducted to investigate the performance benefits of adaptive scanning to optimize the data quality of radar returns. This research focuses on the development and implementation of a waveform agile and adaptive scanning strategy to improve the quality of weather product estimators. Active phased array radars allow radar systems to quickly vary both scan pointing angles and waveform parameters in response to real-time observations of the atmosphere. As an evolution of the previous research effort, this work develops techniques to adaptively change the scan pointing angles, transmit and matched filter waveform parameters to achieve a desired level of data quality. Strategies and techniques are developed to minimize the error between observed and desired data quality measures. Simulation and field experiments are performed to assess the quality of the developed strategies

Advances in real-time thoracic guidance systems

Substantial tissue motion: \u3e1cm) arises in the thoracic/abdominal cavity due to respiration. There are many clinical applications in which localizing tissue with high accuracy: \u3c1mm) is important. Potential applications include radiation therapy, radio frequency ablation, lung/liver biopsies, and brachytherapy seed placement. Recent efforts have made highly accurate sub-mm 3D localization of discrete points available via electromagnetic: EM) position monitoring. Technology from Calypso Medical allows for simultaneous tracking of up to three implanted wireless transponders. Additionally, Medtronic Navigation uses wired electromagnetic tracking to guide surgical tools for image guided surgery: IGS). Utilizing real-time EM position monitoring, a prototype system was developed to guide a therapeutic linear accelerator to follow a moving target: tumor) within the lung/abdomen. In a clinical setting, electromagnetic transponders would be bronchoscopically implanted into the lung of the patient in or near the tumor. These transponders would ax to the lung tissue in a stable manner and allow real-time position knowledge throughout a course of radiation therapy. During each dose of radiation, the beam is either halted when the target is outside of a given threshold, or in a later study the beam follows the target in real-time based on the EM position monitoring. We present quantitative analysis of the accuracy and efficiency of the radiation therapy tumor tracking system. EM tracking shows promise for IGS applications. Tracking the position of the instrument tip allows for minimally invasive intervention and alleviates the trauma associated with conventional surgery. Current clinical IGS implementations are limited to static targets: e.g. craniospinal, neurological, and orthopedic intervention. We present work on the development of a respiratory correlated image guided surgery: RCIGS) system. In the RCIGS system, target positions are modeled via respiratory correlated imaging: 4DCT) coupled with a breathing surrogate representative of the patient\u27s respiratory phase/amplitude. Once the target position is known with respect to the surrogate, intervention can be performed when the target is in the correct location. The RCIGS system consists of imaging techniques and custom developed software to give visual and auditory feedback to the surgeon indicating both the proper location and time for intervention. Presented here are the details of the IGS lung system along with quantitative results of the system accuracy in motion phantom, ex-vivo porcine lung, and human cadaver environments

The phase-switched screen

Conventional (passive) radar-absorbent materials operate either by phase cancellation or by absorbing incident electromagnetic energy and converting it into heat. This paper examines a new type of active "absorber," called the phase-switched screen (PSS). The PSS operates quite differently from passive absorbers in that it exhibits an apparently low value of reflectivity by redistributing the electromagnetic energy incident upon it over a bandwidth that is wide enough to ensure that little reflected energy falls within the pass-band of the receiver. The discussion considers the basic temporal and spectral properties of several PSS topologies, and includes measured data on both planar and cylindrical PSS structures