Perception Of 3d Symmetrical And Near-Symmetrical Shapes, 2017 Purdue University

#### Perception Of 3d Symmetrical And Near-Symmetrical Shapes, Vijai Jayadevan, Aaron Michaux, Edward Delp, Zygmunt Pizlo

*MODVIS Workshop*

No abstract provided.

Color Algebras, 2017 NASA Ames Research Center

Projected Nesterov’S Proximal-Gradient Algorithm For Sparse Signal Recovery, 2017 Iowa State University

#### Projected Nesterov’S Proximal-Gradient Algorithm For Sparse Signal Recovery, Renliang Gu, Aleksandar Dogandžić

*Aleksandar Dogandžić*

We develop a projected Nesterov’s proximal-gradient (PNPG) approach for sparse signal reconstruction that combines adaptive step size with Nesterov’s momentum acceleration. The objective function that we wish to minimize is the sum of a convex differentiable data-fidelity (negative log-likelihood (NLL)) term and a convex regularization term. We apply sparse signal regularization where the signal belongs to a closed convex set within the closure of the domain of the NLL; the convex-set constraint facilitates flexible NLL domains and accurate signal recovery. Signal sparsity is imposed using the l1-norm penalty on the signal’s linear transform coefficients or gradient map ...

Selfish Distributed Compression Over Networks: Correlation Induces Anarchy, 2017 Iowa State University

#### Selfish Distributed Compression Over Networks: Correlation Induces Anarchy, Aditya Ramamoorthy, Vwani Roychowdhury, Sudhir Kumar Singh

*Aditya Ramamoorthy*

We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources ...

The Design Of Efficiently-Encodable Rate-Compatible Ldpc Codes, 2017 Samsung Electronics

#### The Design Of Efficiently-Encodable Rate-Compatible Ldpc Codes, Jaehong Kim, Aditya Ramamoorthy, Steven W. Mclaughlin

*Aditya Ramamoorthy*

We present a new class of irregular low-density parity-check (LDPC) codes for moderate block lengths (up to a few thousand bits) that are well-suited for rate-compatible puncturing. The proposed codes show good performance under puncturing over a wide range of rates and are suitable for usage in incremental redundancy hybrid-automatic repeat request (ARQ) systems. In addition, these codes are linear-time encodable with simple shift-register circuits. For a block length of 1200 bits the codes outperform optimized irregular LDPC codes and extended irregular repeat-accumulate (eIRA) codes for all puncturing rates 0.6~0.9 (base code performance is almost the same ...

On The Multiple-Unicast Capacity Of 3-Source, 3-Terminal Directed Acyclic Networks, 2017 Iowa State University

#### On The Multiple-Unicast Capacity Of 3-Source, 3-Terminal Directed Acyclic Networks, Shurui Huang, Aditya Ramamoorthy

*Aditya Ramamoorthy*

We consider the multiple-unicast problem with three source–terminal pairs over directed acyclic networks with unit-capacity edges. The three – pairs wish to communicate at unitrate via network coding. The connectivity between the – pairs is quantified by means of a connectivity-level vector, such that there exist edge-disjoint paths between and . In this paper, we attempt to classify networks based on the connectivity level. It can be observed that unit-rate transmission can be supported by routing if , for all . In this paper, we consider connectivity-level vectors such that . We present either a constructive linear network coding scheme or an instance of a ...

Minimum Cost Mirror Sites Using Network Coding: Replication Versus Coding At The Source Nodes, 2017 Iowa State University

#### Minimum Cost Mirror Sites Using Network Coding: Replication Versus Coding At The Source Nodes, Shurui Huang, Aditya Ramamoorthy, Muriel Medard

*Aditya Ramamoorthy*

Content distribution over networks is often achieved by using mirror sites that hold copies of files or portions thereof to avoid congestion and delay issues arising from excessive demands to a single location. Accordingly, there are distributed storage solutions that divide the file into pieces and place copies of the pieces (replication) or coded versions of the pieces (coding) at multiple source nodes. We consider a network which uses network coding for multicasting the file. There is a set of source nodes that contains either subsets or coded versions of the pieces of the file. The cost of a given ...

Overlay Protection Against Link Failures Using Network Coding, 2017 Iowa State University

#### Overlay Protection Against Link Failures Using Network Coding, Ahmed Kamal, Aditya Ramamoorthy, Long Long, Shizheng Li

*Aditya Ramamoorthy*

This paper introduces a network coding-based protection scheme against single and multiple link failures. The proposed strategy ensures that in a connection, each node receives two copies of the same data unit: one copy on the working circuit, and a second copy that can be extracted from linear combinations of data units transmitted on a shared protection path. This guarantees instantaneous recovery of data units upon the failure of a working circuit. The strategy can be implemented at an overlay layer, which makes its deployment simple and scalable. While the proposed strategy is similar in spirit to the work of ...

Minimum Cost Distributed Source Coding Over A Network, 2017 Iowa State University

#### Minimum Cost Distributed Source Coding Over A Network, Aditya Ramamoorthy

*Aditya Ramamoorthy*

This work considers the problem of transmitting multiple compressible sources over a network at minimum cost. The aim is to find the optimal rates at which the sources should be compressed and the network flows using which they should be transmitted so that the cost of the transmission is minimal. We consider networks with capacity constraints and linear cost functions. The problem is complicated by the fact that the description of the feasible rate region of distributed source coding problems typically has a number of constraints that is exponential in the number of sources. This renders general purpose solvers inefficient ...

An Achievable Region For The Double Unicast Problem Based On A Minimum Cut Analysis, 2017 Iowa State University

#### An Achievable Region For The Double Unicast Problem Based On A Minimum Cut Analysis, Shurui Huang, Aditya Ramamoorthy

*Aditya Ramamoorthy*

We consider the multiple unicast problem under network coding over directed acyclic networks when there are two source-terminal pairs, s1-t1 and s2-t2. The capacity region for this problem is not known; furthermore, the outer bounds on the region have a large number of inequalities which makes them hard to explicitly evaluate. In this work we consider a related problem. We assume that we only know certain minimum cut values for the network, e.g., mincut(Si, Tj), where Si ⊆ {s1, s2} and Tj ⊆ {t1, t2} for different subsets Si and Tj. Based on these values, we propose an achievable rate ...

Unmanned Aerial Vehicle Tracking System With Out-Of-Sequence Measurement In A Discrete Time-Delayed Extended Kalman Filter, 2017 Utah State University

#### Unmanned Aerial Vehicle Tracking System With Out-Of-Sequence Measurement In A Discrete Time-Delayed Extended Kalman Filter, Roque Lora

*All Graduate Theses and Dissertations*

The goal of this thesis is to extend the delayed Kalman filter so it can be used with non-linear systems and that it can handle randomized delays on the measurements. In the particular case of this study, the filter is used to estimates the states of an unmanned aerial system. The outputs of the filter are used to point an antenna and a camera towards a UAS. Different scenarios are simulated for the purpose of comparing the efficiency of this technique in various situations.

Recursive Robust Pca Or Recursive Sparse Recovery In Large But Structured Noise, 2017 Iowa State University

#### Recursive Robust Pca Or Recursive Sparse Recovery In Large But Structured Noise, Chenlu Qiu, Namrata Vaswani, Brian Lois, Leslie Hogben

*Leslie Hogben*

This paper studies the recursive robust principal components analysis problem. If the outlier is the signal-of-interest, this problem can be interpreted as one of recursively recovering a time sequence of sparse vectors, St, in the presence of large but structured noise, Lt. The structure that we assume on Lt is that Lt is dense and lies in a low-dimensional subspace that is either fixed or changes slowly enough. A key application where this problem occurs is in video surveillance where the goal is to separate a slowly changing background (Lt) from moving foreground objects (St) on-the-fly. To solve the above ...

On The Distance Spectra Of Graphs, 2017 Kharazmi University

#### On The Distance Spectra Of Graphs, Ghodratollah Aalipour, Aida Abiad, Zhanar Berikkyzy, Jay Cummings, Jessica De Silva, Wei Gao, Kristin Heysse, Leslie Hogben, Franklin H.J. Kenter, Jephian C.H. Lin, Michael Tait

*Leslie Hogben*

The distance matrix of a graph *G* is the matrix containing the pairwise distances between vertices. The distance eigenvalues of *G* are the eigenvalues of its distance matrix and they form the distance spectrum of *G*. We determine the distance spectra of double odd graphs and Doob graphs, completing the determination of distance spectra of distance regular graphs having exactly one positive distance eigenvalue. We characterize strongly regular graphs having more positive than negative distance eigenvalues. We give examples of graphs with few distinct distance eigenvalues but lacking regularity properties. We also determine the determinant and inertia of the distance ...

Recursive Robust Pca Or Recursive Sparse Recovery In Large But Structured Noise, 2017 Iowa State University

#### Recursive Robust Pca Or Recursive Sparse Recovery In Large But Structured Noise, Chenlu Qiu, Namrata Vaswani, Brian Lois, Leslie Hogben

*Leslie Hogben*

This paper studies the recursive robust principal components analysis problem. If the outlier is the signal-of-interest, this problem can be interpreted as one of recursively recovering a time sequence of sparse vectors, St, in the presence of large but structured noise, Lt. The structure that we assume on Lt is that Lt is dense and lies in a low-dimensional subspace that is either fixed or changes slowly enough. A key application where this problem occurs is in video surveillance where the goal is to separate a slowly changing background (Lt) from moving foreground objects (St) on-the-fly. To solve the above ...

T1, T2, And Off-Resonance Mapping Using A Non-Linear Least-Squares Fit Of The Bssfp Signal, 2017 Brigham Young University

#### T1, T2, And Off-Resonance Mapping Using A Non-Linear Least-Squares Fit Of The Bssfp Signal, Meredith Taylor, Joseph Valentine, Steven Whitaker, Neal Bangerter

*Biomedical Engineering Western Regional Conference*

The mapping of MR relaxation times has found a broad variety of applications in the study of disease. Unfortunately, the gold standards for acquiring T_{1} and T_{2} maps require long scan times, and are therefore more suited to 2D acquisitions with limited slices. For reasonable scan times, resolution is limited making these scans less useful for showing fine morphological detail. A rapid 3D sequence at higher resolutions that could be used to provide both morphological detail and relaxation time maps would be particularly useful. We propose a technique with potential to provide simultaneous band-free 3D datasets and estimates ...

Water Fat Separation With Multiple-Acquisition Bssfp Mri, 2017 Brigham Young University

#### Water Fat Separation With Multiple-Acquisition Bssfp Mri, Michael A. Mendoza 8232743, Joseph Valentine, Neal Bangerter

*Biomedical Engineering Western Regional Conference*

We present a technique that combines the advantages of bSSFP MRI with Dixon reconstruction in order to produce robust water fat separation with high SNR in a short imaging time, while simultaneously reducing banding artifacts that traditionally degrade image quality.

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, 2017 University of Massachusetts - Amherst

#### Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

*Masters Theses May 2014 - current*

Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.

State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to ...

Kasi: A Ka-Band And S-Band Cross-Track Interferometer, 2017 University of Massachusetts - Amherst

#### Kasi: A Ka-Band And S-Band Cross-Track Interferometer, Gerard Ruiz Carregal

*Masters Theses May 2014 - current*

A dual-frequency system is needed to better understand natural processes that constitute the environment and seasonal cycles of the Earth. A system working at two different wavelengths acquiring data simultaneously will give a valuable dataset since the conditions on the ground will be exactly the same. Hence, elements such as wind, soil moisture or any other changes on the ground will not interfere in the mea- surements. This thesis explains how an S-band radar was built and tested. Moreover, the experiments done with a Ka-band radar used as a scatterometer are explained as well as the data processing and analysis ...

Time Domain Sar Processing With Gpus For Airborne Platforms, 2017 University of Massachusetts - Amherst

#### Time Domain Sar Processing With Gpus For Airborne Platforms, Dustin Lagoy

*Masters Theses May 2014 - current*

A time-domain backprojection processor for airborne synthetic aperture radar (SAR) has been developed at the University of Massachusetts’ Microwave Remote Sensing Lab (MIRSL). The aim of this work is to produce a SAR processor capable of addressing the motion compensation issues faced by frequency-domain processing algorithms, in order to create well focused SAR imagery suitable for interferometry. The time-domain backprojection algorithm inherently compensates for non-linear platform motion, dependent on the availability of accurate measurements of the motion. The implementation must manage the relatively high computational burden of the backprojection algorithm, which is done using modern graphics processing units (GPUs), programmed ...

Topography Measurements Using An Airborne Ka-Band Fmcw Interferometric Synthetic Aperture Radar, 2017 University of Massachusetts - Amherst

#### Topography Measurements Using An Airborne Ka-Band Fmcw Interferometric Synthetic Aperture Radar, Kan Fu

*Doctoral Dissertations May 2014 - current*

Radar interferometry at millimeter-wave frequencies has the ability of topography measurement of different types of terrain, such as water surfaces and tree canopies. A Ka-band interferometric radar was mounted on an airborne platform, and flown over the Connecticut river region in western Massachusetts near Amherst on June 11, 2012. More than 20 Gigabytes of raw data was recorded. This dissertation outline presents the results of the data processing, which includes (1) the estimation and removal of the embedded high frequency phase error in the raw data; (2) the synthetic aperture processing; (3) the interferometric processing. The digital elevation model (DEM ...