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Signals, Volume 2, Issue 2 (June 2021) – 11 articles

Cover Story (view full-size image): Many content-based music retrieval strategies follow the query-by-example paradigm, where the user provides a query audio snippet, and the retrieval system returns recordings from a music collection that are similar to the query. In this scenario, a fast response from the system is essential for a positive user experience. We describe how to improve the efficiency of the search by using a modern graph-based index, denoted as the Hierarchical Navigable Small World (HNSW) graph. As our main contribution, we explore its potential in the context of a cross-version music retrieval application. We show that the HNSW-based retrieval is several orders of magnitude faster than previous music retrieval approaches, highlighting the practical relevance of the HNSW graph for music information retrieval applications. View this paper
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12 pages, 3605 KiB  
Article
Optimization of the Unambiguity of Cross-Correlated Ultrasonic Signals through Coded Excitation Sequences for Robust Time-of-Flight Measurements
by Marius Schäfer, Hendrik Theado, Michael M. Becker and Sarah C. L. Fischer
Signals 2021, 2(2), 366-377; https://doi.org/10.3390/signals2020023 - 16 Jun 2021
Cited by 3 | Viewed by 2523
Abstract
The cross-correlation function (CCF) is an established technique to calculate time-of-flight for ultrasonic signals. However, the quality of the CCF depends on the shape of the input signals. In many use cases, the CCF can exhibit secondary maxima in the same order of [...] Read more.
The cross-correlation function (CCF) is an established technique to calculate time-of-flight for ultrasonic signals. However, the quality of the CCF depends on the shape of the input signals. In many use cases, the CCF can exhibit secondary maxima in the same order of magnitude as the main maximum, making its interpretation less robust against external disturbances. This paper describes an approach to optimize ultrasonic signals for time-of-flight measurements through coded excitation sequences. The main challenge for applying coded excitation sequences to ultrasonic signals is the influence of the piezoelectric transducer on the outgoing signal. Thus, a simulation model to describe the transfer function of an experimental setup was developed and validated with common code sequences such as pseudo noise sequences (PN), Barker codes and chirp signals. Based on this model an automated optimization of ultrasonic echoes was conducted with random generated sequences, resulting in a decrease in the secondary positive maximum of the CCF to 56.6%. Based on these results, further empiric optimization leveraging the nonlinear regime of the piezoelectric transducer resulted in an even lower secondary positive maximum of the CCF with a height of 25% of the first maximum. Experiments were conducted on different samples to show that the findings hold true for small variations in the experimental setup; however, further work is necessary to develop transfer functions and simulations able to include a wider parameter space, such as varying transducer types or part geometry. Full article
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13 pages, 915 KiB  
Article
Dynamic Functional Principal Components for Testing Causality
by Matthieu Saumard and Bilal Hadjadji
Signals 2021, 2(2), 353-365; https://doi.org/10.3390/signals2020022 - 8 Jun 2021
Viewed by 2397
Abstract
In this paper, we investigate the causality in the sense of Granger for functional time series. The concept of causality for functional time series is defined, and a statistical procedure of testing the hypothesis of non-causality is proposed. The procedure is based on [...] Read more.
In this paper, we investigate the causality in the sense of Granger for functional time series. The concept of causality for functional time series is defined, and a statistical procedure of testing the hypothesis of non-causality is proposed. The procedure is based on projections on dynamic functional principal components and the use of a multivariate Granger test. A comparative study with existing procedures shows the good results of our test. An illustration on a real dataset is provided to attest the performance of the proposed procedure. Full article
(This article belongs to the Special Issue Signal Processing and Time-Frequency Analysis)
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17 pages, 1601 KiB  
Article
Efficient Retrieval of Music Recordings Using Graph-Based Index Structures
by Frank Zalkow, Julian Brandner and Meinard Müller
Signals 2021, 2(2), 336-352; https://doi.org/10.3390/signals2020021 - 17 May 2021
Cited by 2 | Viewed by 8125
Abstract
Flexible retrieval systems are required for conveniently browsing through large music collections. In a particular content-based music retrieval scenario, the user provides a query audio snippet, and the retrieval system returns music recordings from the collection that are similar to the query. In [...] Read more.
Flexible retrieval systems are required for conveniently browsing through large music collections. In a particular content-based music retrieval scenario, the user provides a query audio snippet, and the retrieval system returns music recordings from the collection that are similar to the query. In this scenario, a fast response from the system is essential for a positive user experience. For realizing low response times, one requires index structures that facilitate efficient search operations. One such index structure is the K-d tree, which has already been used in music retrieval systems. As an alternative, we propose to use a modern graph-based index, denoted as Hierarchical Navigable Small World (HNSW) graph. As our main contribution, we explore its potential in the context of a cross-version music retrieval application. In particular, we report on systematic experiments comparing graph- and tree-based index structures in terms of the retrieval quality, disk space requirements, and runtimes. Despite the fact that the HNSW index provides only an approximate solution to the nearest neighbor search problem, we demonstrate that it has almost no negative impact on the retrieval quality in our application. As our main result, we show that the HNSW-based retrieval is several orders of magnitude faster. Furthermore, the graph structure also works well with high-dimensional index items, unlike the tree-based structure. Given these merits, we highlight the practical relevance of the HNSW graph for music information retrieval (MIR) applications. Full article
(This article belongs to the Special Issue Advances in Processing and Understanding of Music Signals)
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32 pages, 5734 KiB  
Article
Fluorescent Imaging and Multifusion Segmentation for Enhanced Visualization and Delineation of Glioblastomas Margins
by Aditi Deshpande, Thomas Cambria, Charles Barnes, Alexandros Kerwick, George Livanos, Michalis Zervakis, Anthony Beninati, Nicolas Douard, Martin Nowak, James Basilion, Jennifer L. Cutter, Gloria Bauman, Suman Shrestha, Zoe Giakos, Wafa Elmannai, Yi Wang, Paniz Foroutan, Tannaz Farrahi and George C. Giakos
Signals 2021, 2(2), 304-335; https://doi.org/10.3390/signals2020020 - 13 May 2021
Cited by 2 | Viewed by 3041
Abstract
This study investigates the potential of fluorescence imaging in conjunction with an original, fused segmentation framework for enhanced detection and delineation of brain tumor margins. By means of a test bed optical microscopy system, autofluorescence is utilized to capture gray level images of [...] Read more.
This study investigates the potential of fluorescence imaging in conjunction with an original, fused segmentation framework for enhanced detection and delineation of brain tumor margins. By means of a test bed optical microscopy system, autofluorescence is utilized to capture gray level images of brain tumor specimens through slices, obtained at various depths from the surface, each of 10 µm thickness. The samples used in this study originate from tumor cell lines characterized as Gli36ϑEGRF cells expressing a green fluorescent protein. An innovative three-step biomedical image analysis framework is presented aimed at enhancing the contrast and dissimilarity between the malignant and the remaining tissue regions to allow for enhanced visualization and accurate extraction of tumor boundaries. The fluorescence image acquisition system implemented with an appropriate unsupervised pipeline of image processing and fusion algorithms indicates clear differentiation of tumor margins and increased image contrast. Establishing protocols for the safe administration of fluorescent protein molecules, these would be introduced into glioma tissues or cells either at a pre-surgery stage or applied to the malignant tissue intraoperatively; typical applications encompass areas of fluorescence-guided surgery (FGS) and confocal laser endomicroscopy (CLE). As a result, this image acquisition scheme could significantly improve decision-making during brain tumor resection procedures and significantly facilitate brain surgery neuropathology during operation. Full article
(This article belongs to the Special Issue Biosignals Processing and Analysis in Biomedicine)
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18 pages, 12808 KiB  
Article
Recovering Texture with a Denoising-Process-Aware LMMSE Filter
by Yuta Saito and Takamichi Miyata
Signals 2021, 2(2), 286-303; https://doi.org/10.3390/signals2020019 - 11 May 2021
Cited by 2 | Viewed by 2483
Abstract
Image denoising methods generally remove not only noise but also fine-scale textures and thus degrade the subjective image quality. In this paper, we propose a method of recovering the texture component that is lost under a state-of-the-art denoising method called weighted nuclear norm [...] Read more.
Image denoising methods generally remove not only noise but also fine-scale textures and thus degrade the subjective image quality. In this paper, we propose a method of recovering the texture component that is lost under a state-of-the-art denoising method called weighted nuclear norm minimization (WNNM). We recover the image texture with a linear minimum mean squared error estimator (LMMSE filter), which requires statistical information about the texture and noise. This requirement is the key problem preventing the application of the LMMSE filter for texture recovery because such information is not easily obtained. We propose a new method of estimating the necessary statistical information using Stein’s lemma and several assumptions and show that our estimated information is more accurate than the simple estimation in terms of the Fréchet distance. Experimental results show that our proposed method can improve the objective quality of denoised images. Moreover, we show that our proposed method can also improve the subjective quality when an additional parameter is chosen for the texture to be added. Full article
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41 pages, 4626 KiB  
Review
An Educational Guide through the FMP Notebooks for Teaching and Learning Fundamentals of Music Processing
by Meinard Müller
Signals 2021, 2(2), 245-285; https://doi.org/10.3390/signals2020018 - 30 Apr 2021
Cited by 8 | Viewed by 4814
Abstract
This paper provides a guide through the FMP notebooks, a comprehensive collection of educational material for teaching and learning fundamentals of music processing (FMP) with a particular focus on the audio domain. Organized in nine parts that consist of more than 100 individual [...] Read more.
This paper provides a guide through the FMP notebooks, a comprehensive collection of educational material for teaching and learning fundamentals of music processing (FMP) with a particular focus on the audio domain. Organized in nine parts that consist of more than 100 individual notebooks, this collection discusses well-established topics in music information retrieval (MIR) such as beat tracking, chord recognition, music synchronization, audio fingerprinting, music segmentation, and source separation, to name a few. These MIR tasks provide motivating and tangible examples that students can hold onto when studying technical aspects in signal processing, information retrieval, or pattern analysis. The FMP notebooks comprise detailed textbook-like explanations of central techniques and algorithms combined with Python code examples that illustrate how to implement the methods. All components, including the introductions of MIR scenarios, illustrations, sound examples, technical concepts, mathematical details, and code examples, are integrated into a unified framework based on Jupyter notebooks. Providing a platform with many baseline implementations, the FMP notebooks are suited for conducting experiments and generating educational material for lectures, thus addressing students, teachers, and researchers. While giving a guide through the notebooks, this paper’s objective is to yield concrete examples on how to use the FMP notebooks to create an enriching, interactive, and interdisciplinary supplement for studies in science, technology, engineering, and mathematics. The FMP notebooks (including HTML exports) are publicly accessible under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Full article
(This article belongs to the Special Issue Advances in Processing and Understanding of Music Signals)
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20 pages, 2016 KiB  
Article
A Numerical Study on Computational Time Reversal for Structural Health Monitoring
by Christos G. Panagiotopoulos and Georgios E. Stavroulakis
Signals 2021, 2(2), 225-244; https://doi.org/10.3390/signals2020017 - 22 Apr 2021
Cited by 2 | Viewed by 2602
Abstract
Structural health monitoring problems are studied numerically with the time reversal method (TR). The dynamic output of the structure is applied, time reversed, as an external loading and its propagation within the deformable medium is followed backwards in time. Unknown loading sources or [...] Read more.
Structural health monitoring problems are studied numerically with the time reversal method (TR). The dynamic output of the structure is applied, time reversed, as an external loading and its propagation within the deformable medium is followed backwards in time. Unknown loading sources or damages can be discovered by means of this method, focused by the reversed signal. The method is theoretically justified by the time-reversibility of the wave equation. Damage identification problems relevant to structural health monitoring for truss and frame structures are studied here. Beam structures are used for the demonstration of the concept, by means of numerical experiments. The influence of the signal-to-noise ratio (SNR) on the results was investigated, since this quantity influences the applicability of the method in real-life cases. The method is promising, in view of the increasing availability of distributed intelligent sensors and actuators. Full article
(This article belongs to the Special Issue Advanced Signal/Data Processing for Structural Health Monitoring)
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24 pages, 2698 KiB  
Article
A Study on the Essential and Parkinson’s Arm Tremor Classification
by Vasileios Skaramagkas, George Andrikopoulos, Zinovia Kefalopoulou and Panagiotis Polychronopoulos
Signals 2021, 2(2), 201-224; https://doi.org/10.3390/signals2020016 - 19 Apr 2021
Cited by 7 | Viewed by 4083
Abstract
In this article, the challenge of discriminating between essential and Parkinson’s tremor is addressed. Although a variety of methods have been proposed for diagnosing the severity of these highly occurring tremor types, their rapid and effective identification, especially in their early stages, proves [...] Read more.
In this article, the challenge of discriminating between essential and Parkinson’s tremor is addressed. Although a variety of methods have been proposed for diagnosing the severity of these highly occurring tremor types, their rapid and effective identification, especially in their early stages, proves particularly difficult and complicated due to their wide range of causes and similarity of symptoms. To this goal, a clinical analysis was performed, where a number of volunteers including essential and Parkinson’s tremor-diagnosed patients underwent a series of pre-defined motion patterns, during which a wearable sensing setup was used to measure their lower arm tremor characteristics from multiple selected points. Extracted features from the acquired accelerometer signals were used to train classification algorithms, including decision trees, discriminant analysis, support vector machine (SVM), K-nearest neighbor (KNN) and ensemble learning algorithms, for providing a comparative study and evaluating the potential of utilizing machine learning to accurately discriminate among different tremor types. Overall, SVM related classifiers proved to be the most successful in terms of classifying between Parkinson’s, essential and no tremor diagnosed with percentages reaching up to 100% for a single accelerometer measurement at the metacarpal area. In general and in motion while holding an object position, Coarse Gaussian SVM classifier reached 82.62% accuracy. Full article
(This article belongs to the Special Issue Biosignals Processing and Analysis in Biomedicine)
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12 pages, 1452 KiB  
Article
Adaptive Sparse Cyclic Coordinate Descent for Sparse Frequency Estimation
by Yuneisy E. Garcia Guzman and Michael Lunglmayr
Signals 2021, 2(2), 189-200; https://doi.org/10.3390/signals2020015 - 15 Apr 2021
Cited by 1 | Viewed by 2047
Abstract
The frequency estimation of multiple complex sinusoids in the presence of noise is important for many signal processing applications. As already discussed in the literature, this problem can be reformulated as a sparse representation problem. In this letter, such a formulation is derived [...] Read more.
The frequency estimation of multiple complex sinusoids in the presence of noise is important for many signal processing applications. As already discussed in the literature, this problem can be reformulated as a sparse representation problem. In this letter, such a formulation is derived and an algorithm based on sparse cyclic coordinate descent (SCCD) for estimating the frequency parameters is proposed. The algorithm adaptively reduces the size of the used frequency grid, which eases the computational burden. Simulation results revealed that the proposed algorithm achieves similar performance to the original formulation and the Root-multiple signal classification (MUSIC) algorithm in terms of the mean square error (MSE), with significantly less complexity. Full article
(This article belongs to the Special Issue Signal Processing and Time-Frequency Analysis)
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15 pages, 1228 KiB  
Article
Trajectory Optimisation for Cooperative Target Tracking with Passive Mobile Sensors
by Xuezhi Wang, Branko Ristic, Braham Himed and Bill Moran
Signals 2021, 2(2), 174-188; https://doi.org/10.3390/signals2020014 - 7 Apr 2021
Cited by 4 | Viewed by 2222
Abstract
The paper considers the problem of tracking a moving target using a pair of cooperative bearing-only mobile sensors. Sensor trajectory optimisation plays the central role in this problem, with the objective to minimize the estimation error of the target state. Two approximate closed-form [...] Read more.
The paper considers the problem of tracking a moving target using a pair of cooperative bearing-only mobile sensors. Sensor trajectory optimisation plays the central role in this problem, with the objective to minimize the estimation error of the target state. Two approximate closed-form statistical reward functions, referred to as the Expected Rényi information divergence (RID) and the Determinant of the Fisher Information Matrix (FIM), are analysed and discussed in the paper. Being available analytically, the two reward functions are fast to compute and therefore potentially useful for longer horizon sensor trajectory planning. The paper demonstrates, both numerically and from the information geometric viewpoint, that the Determinant of the FIM is a superior reward function. The problem with the Expected RID is that the approximation involved in its derivation significantly reduces the correlation between the target state estimates at two sensors, and consequently results in poorer performance. Full article
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15 pages, 1734 KiB  
Article
A Termination Criterion for Probabilistic Point Clouds Registration
by Simone Fontana and Domenico Giorgio Sorrenti
Signals 2021, 2(2), 159-173; https://doi.org/10.3390/signals2020013 - 24 Mar 2021
Viewed by 2044
Abstract
Probabilistic Point Clouds Registration (PPCR) is an algorithm that, in its multi-iteration version, outperformed state-of-the-art algorithms for local point clouds registration. However, its performances have been tested using a fixed high number of iterations. To be of practical usefulness, we think that the [...] Read more.
Probabilistic Point Clouds Registration (PPCR) is an algorithm that, in its multi-iteration version, outperformed state-of-the-art algorithms for local point clouds registration. However, its performances have been tested using a fixed high number of iterations. To be of practical usefulness, we think that the algorithm should decide by itself when to stop, on one hand to avoid an excessive number of iterations and waste computational time, on the other to avoid getting a sub-optimal registration. With this work, we compare different termination criteria on several datasets, and prove that the chosen one produces very good results that are comparable to those obtained using a very large number of iterations, while saving computational time. Full article
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