# Electrical Engineering and Systems Science

## New submissions

[ total of 17 entries: 1-17 ]
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### New submissions for Tue, 20 Mar 18

[1]
Title: A Novel Blaschke Unwinding Adaptive Fourier Decomposition based Signal Compression Algorithm with Application on ECG Signals
Subjects: Signal Processing (eess.SP); Data Analysis, Statistics and Probability (physics.data-an); Machine Learning (stat.ML)

This paper presents a novel signal compression algorithm based on the Blaschke unwinding adaptive Fourier decomposition (AFD). The Blaschke unwinding AFD is a newly developed signal decomposition theory. It utilizes the Nevanlinna factorization and the maximal selection principle in each decomposition step, and achieves a faster convergence rate with higher fidelity. The proposed compression algorithm is applied to the electrocardiogram signal. To assess the performance of the proposed compression algorithm, in addition to the generic assessment criteria, we consider the less discussed criteria related to the clinical needs -- for the heart rate variability analysis purpose, how accurate the R peak information is preserved is evaluated. The experiments are conducted on the MIT-BIH arrhythmia benchmark database. The results show that the proposed algorithm performs better than other state-of-the-art approaches. Meanwhile, it also well preserves the R peak information.

[2]
Title: Example-based super-resolution for point-cloud video
Comments: This paper was submitted to ICIP-2018 and its copyright may be transferred to IEEE. Work partially supported by CNPq under grant 308150/2014-7
Subjects: Signal Processing (eess.SP)

We propose a mixed-resolution point-cloud representation and an example-based super-resolution framework, from which several processing tools can be derived, such as compression, denoising and error concealment. By inferring the high-frequency content of low-resolution frames based on the similarities between adjacent full-resolution frames, the proposed framework achieves an average 1.18 dB gain over low-pass versions of the point-cloud, for a projection-based distortion metric[1-2].

[3]
Title: Non-reciprocal Components Based on Switched Transmission Lines
Comments: 17 pages, 24 figures, TMTT, under review
Subjects: Signal Processing (eess.SP)

Non-reciprocal components, such as isolators and circulators, are critical to wireless communication and radar applications. Traditionally, non-reciprocal components have been implemented using ferrite materials, which exhibit non-reciprocity under the influence of an external magnetic field. However, ferrite materials cannot be integrated into IC fabrication processes, and consequently are bulky and expensive. In the recent past, there has been strong interest in achieving non-reciprocity in a non-magnetic IC-compatible fashion using spatio-temporal modulation. In this paper, we present a general approach to non-reciprocity based on switched transmission lines. Switched transmission lines enable broadband, lossless and compact non-reciprocity, and a wide range of non-reciprocal functionalities, including non-reciprocal phase shifters, ultra-broadband gyrators and isolators, frequency-conversion isolators, and high-linearity/high-frequency/ultra-broadband circulators. We present a detailed theoretical analysis of the various non-idealities that impact insertion loss and provide design guidelines. The theory is validated by experimental results from discrete-component-based gyrators and isolators, and a 25GHz circulator fabricated in 45nm SOI CMOS technology.

[4]
Title: Directional emphasis in ambisonics
Subjects: Audio and Speech Processing (eess.AS); Sound (cs.SD)

We describe an ambisonics enhancement method that increases the signal strength in specified directions at low computational cost. The method can be used in a static setup to emphasize the signal arriving from a particular direction or set of directions, much like a spotlight amplifies the visibility of objects. It can also be used in an adaptive arrangement where it sharpens directionality and reduces the distortion in timbre associated with low-degree ambisonics representations. The emphasis operator has very low computational complexity and can be applied to time-domain as well as time-frequency ambisonics representations. The operator maps a low-degree ambisonics representation into a higher degree representation.

[5]
Title: Learning to Coordinate in a Decentralized Cognitive Radio Network in Presence of Jammers
Subjects: Signal Processing (eess.SP)

Efficient utilization of licensed spectrum in the cognitive radio network is challenging due to lack of coordination among the Secondary Users (SUs). Distributed algorithms proposed in the literature aim to maximize the network throughput by ensuring orthogonal channel allocation for the SUs. However, these algorithms work under the assumption that all the SUs faithfully follow the algorithms which may not always hold due to the decentralized nature of the network. In this paper, we study distributed algorithms that are robust against malicious behavior (jamming attack). We consider both the cases of jammers launching coordinated and uncoordinated attacks. In the coordinated attack, the jammers select non-overlapping channels to attack in each time slot and can significantly increase the number of collisions for SUs. We setup the problem in each scenario as a multi-player bandit and develop algorithms. The analysis shows that when the SUs faithfully implement proposed algorithms, the regret is constant with high probability. We validate our claims through exhaustive synthetic experiments and also through a realistic USRP based experiments.

[6]
Title: NLOS Mitigation Using Sparsity Feature And Iterative Methods
Subjects: Signal Processing (eess.SP)

Well-known methods are employed to localize mobile station (MS) using line of sight (LOS) measurements. These methods may result in large error if they are fed with non LOS (NLOS) measurements. Our proposed algorithm, referred to as Sparse Recovery of NLOS using IMAT (SRNI), considers NLOS as unknown variables and solves the resultant underdetermined system emphasizing on its sparsity feature based on IMAT methods. Simulations are conducted to investigate the performance of SRNI in comparison of other conventional algorithms. Results demonstrate that SRNI is fast enough to deal with large combination of BSs and also accurate in lower number of BSs

[7]
Title: Dynamics and Stability of Meshed Multiterminal HVDC Networks
Subjects: Signal Processing (eess.SP)

This paper investigates the existence of an equilibrium point in multiterminal HVDC (MT-HVDC) grids, assesses its uniqueness and defines conditions to ensure its stability. An offshore MT-HVDC system including two wind farms is selected as application test case. At first, a generalized dynamic model of the network is proposed, using hypergraph theory. Such model captures the frequency dependence of transmission lines and cables, it is non-linear due to the constant power behavior of the converter terminals using droop regulation, and presents a suitable degree of simplifications of the MMC converters, under given conditions, to allow system level studies over potentially large networks. Based on this model, the existence and uniqueness of the equilibrium point is demonstrated by returning the analysis to a load-flow problem and using the Banach fixed point theorem. Additionally, the stability of the equilibrium is analyzed by obtaining a Lyapunov function by the Krasovskii's theorem. Computational results obtained for the selected 4 terminals MT-HVDC grid corroborate the requirement for the existence and stability of the equilibrium point.

[8]
Title: Cellular and WiFi Co-design for 5G User Equipment
Subjects: Signal Processing (eess.SP)

Motivated by providing solutions to design challenges of coexisting cellular and WiFi for future 5G application scenarios, this paper, first, conducts an in-depth investigation of current technological trends of 5G from user equipment (UE) design perspective, and then presents a cost-effective cellular-WiFi design methodology based on the new distributed phased array MIMO (DPA-MIMO) architecture for practical 5G UE devices as an example. Furthermore, additional 5G cellular-WiFi application scenarios and co-operation details within 5G heterogeneous networks are unveiled on top of the said cellular-WiFi co-enabled 5G UE design.

### Cross-lists for Tue, 20 Mar 18

[9]  arXiv:1803.06480 (cross-list from cs.CV) [pdf, other]
Title: Queuing Theory Guided Intelligent Traffic Scheduling through Video Analysis using Dirichlet Process Mixture Model
Subjects: Computer Vision and Pattern Recognition (cs.CV); Image and Video Processing (eess.IV)

Accurate prediction of traffic signal duration for roadway junction is a challenging problem due to the dynamic nature of traffic flows. Though supervised learning can be used, parameters may vary across roadway junctions. In this paper, we present a computer vision guided expert system that can learn the departure rate of a given traffic junction modeled using traditional queuing theory. First, we temporally group the optical flow of the moving vehicles using Dirichlet Process Mixture Model (DPMM). These groups are referred to as tracklets or temporal clusters. Tracklet features are then used to learn the dynamic behavior of a traffic junction, especially during on/off cycles of a signal. The proposed queuing theory based approach can predict the signal open duration for the next cycle with higher accuracy when compared with other popular features used for tracking. The hypothesis has been verified on two publicly available video datasets. The results reveal that the DPMM based features are better than existing tracking frameworks to estimate $\mu$. Thus, signal duration prediction is more accurate when tested on these datasets.The method can be used for designing intelligent operator-independent traffic control systems for roadway junctions at cities and highways.

[10]  arXiv:1803.06554 (cross-list from cs.CV) [pdf, other]
Title: Fusion of an Ensemble of Augmented Image Detectors for Robust Object Detection
Comments: 21 pages, 12 figures, journal paper, MDPI Sensors, 2018
Subjects: Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI); Image and Video Processing (eess.IV)

A significant challenge in object detection is accurate identification of an object's position in image space, whereas one algorithm with one set of parameters is usually not enough, and the fusion of multiple algorithms and/or parameters can lead to more robust results. Herein, a new computational intelligence fusion approach based on the dynamic analysis of agreement among object detection outputs is proposed. Furthermore, we propose an online versus just in training image augmentation strategy. Experiments comparing the results both with and without fusion are presented. We demonstrate that the augmented and fused combination results are the best, with respect to higher accuracy rates and reduction of outlier influences. The approach is demonstrated in the context of cone, pedestrian and box detection for Advanced Driver Assistance Systems (ADAS) applications.

[11]  arXiv:1803.06871 (cross-list from cs.IT) [pdf, ps, other]
Title: Symbol-Level Precoding Design for Max-Min SINR in Multiuser MISO Broadcast Channels
Comments: Submitted to SPAWC 2018, 7 pages, 2 figures
Subjects: Information Theory (cs.IT); Signal Processing (eess.SP)

In this paper, we address the symbol level precoding (SLP) design problem under max-min SINR criterion in the downlink of multiuser multiple-input single-output (MISO) channels. First, we show that the distance preserving constructive interference regions (DPCIR) are always polyhedral angles (shifted pointed cones) for any given constellation point with unbounded decision region. Then we prove that any signal in a given unbounded DPCIR has a norm larger than the norm of the corresponding vertex if and only if the convex hull of the constellation contains the origin. Using these properties, we show that the power of the noiseless received signal lying on an unbounded DPCIR is an strictly increasing function of two parameters. This allows us to reformulate the originally non-convex SLP max-min SINR as a convex optimization problem. We discuss the loss due to our proposed convex reformulation and provide some simulation results.

[12]  arXiv:1803.07065 (cross-list from physics.app-ph) [pdf]
Title: Sensorless Resonance Tracking of Resonant Electromagnetic Actuator through Back-EMF Estimation for Mobile Devices
Authors: Youngjun Cho
Subjects: Applied Physics (physics.app-ph); Systems and Control (cs.SY); Signal Processing (eess.SP); Dynamical Systems (math.DS)

Resonant electromagnetic actuators have been broadly used as vibration motors for mobile devices given their ability of generating relatively fast, strong, and controllable vibration force at a given resonant frequency. Mechanism of the actuators that is based on mechanical resonance, however, limits their use to a situation where their resonant frequencies are known and unshifted. In reality, there are many factors that alter the resonant frequency: for example, manufacturing tolerances, worn mechanical components such as a spring, nonlinearity in association with different input voltage levels. Here, we describe a sensorless resonance tracking method that actuates the motor and automatically detects its unknown damped natural frequency through the estimation of back electromotive force (EMF) and inner mass movements. We demonstrate the tracking performance of the proposed method through a series of experiments. This approach has the potential to control residual vibrations and then improve vibrotactile feedback, which can potentially be used for human-computer interaction, cognitive and affective neuroscience research.

### Replacements for Tue, 20 Mar 18

[13]  arXiv:1710.11439 (replaced) [pdf, other]
Title: Statistical Speech Enhancement Based on Probabilistic Integration of Variational Autoencoder and Non-Negative Matrix Factorization
Comments: 5 pages, 3 figures, version that Eqs. (9), (19), and (20) in v2 (submitted to ICASSP 2018) are corrected. Samples available here: this http URL
Subjects: Sound (cs.SD); Learning (cs.LG); Audio and Speech Processing (eess.AS); Machine Learning (stat.ML)
[14]  arXiv:1803.01417 (replaced) [pdf]
Title: Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected Network
Comments: 10 pages, 2 figures, 2 tables. submitted to MICCAI 2018. v2 fixed network figures and some minor typos
Subjects: Computer Vision and Pattern Recognition (cs.CV); Image and Video Processing (eess.IV)
[15]  arXiv:1803.01897 (replaced) [pdf]
Title: Adaptive Matching Pursuit based Online Identification and Control Scheme for Nonlinear Systems
Subjects: Signal Processing (eess.SP)
[16]  arXiv:1803.04092 (replaced) [pdf, other]
Title: Estimating Shape of Target Object Moving on Unknown Trajectory by Using Location-Unknown Distance Sensors: Theoretical Framework
Comments: 11 pages, 13 figures, and 7 tables
Subjects: Signal Processing (eess.SP)
[17]  arXiv:1803.04315 (replaced) [pdf, other]
Title: Power-Efficient Deployment of UAVs as Relays
Authors: Erdem Koyuncu
Subjects: Information Theory (cs.IT); Signal Processing (eess.SP)
[ total of 17 entries: 1-17 ]
[ showing up to 2000 entries per page: fewer | more ]

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