Reproducible Research in Signal Processing

Reproducible research results become more and more an important issue as systems under investigation are growing permanently in complexity, and it becomes thus almost impossible to judge the accuracy of research results merely on the bare paper presentation.Peer ReviewedPreprin

Experiences with Reproducible Research in Various Facets of Signal Processing Research

How often have you been able to implement an algorithm as it is described in a paper? And when you did, were you confident that you had exactly the same parameter values and results as the authors of the paper? All too often, articles do not describe all the details of an algorithm and thus prohibit an implementation by someone else. In this paper, we describe our experience with reproducible research, a paradigm to allow other people to reproduce with minimal effort the results we have obtained. We discuss both the reproducibility of data and algorithms, and give examples for each of them. The effort required to make research reproducible is compensated by a higher visibility and impact of the results

Hardware And Software For Reproducible Research In Audio Array Signal Processing

In our demo, we present two hardware platforms for prototyping audio array signal processing. Pyramic is a 48-channel microphone array fitted on an FPGA and Compact Six is a portable microphone array with six microphones, closer to the technical constraints of consumer electronics. A browser based interface was developed that allows the user to interact with the audio stream from the arrays in real time. The software component of this demo is a Python module with implementations of basic audio signal processing blocks and popular techniques like STFT, beamforming, and DoA. Both the hardware design files and the software are open source and freely shared. As part of a collaboration with IBM Research, their beamforming and imaging technologies will also be portrayed. The hardware will be demonstrated through an installation processing the microphone signals into light patterns on a circular LED array. The demo will be interactive and let visitors play with different algorithms for DoA (SRP, FRIDA [1], Bluebild) and beamforming (MVDR, Flexibeam [2]). The availability of an open platform with reference implementations encourages reproducible research and minimizes setup-time when testing and benchmarking new audio array signal processing algorithms. It can also serve as a useful educational tool, providing a means to work with real-life signals

Making neurophysiological data analysis reproducible. Why and how?

Manuscript submitted to "The Journal of Physiology (Paris)". Second version.Reproducible data analysis is an approach aiming at complementing classical printed scientific articles with everything required to independently reproduce the results they present. ''Everything'' covers here: the data, the computer codes and a precise description of how the code was applied to the data. A brief history of this approach is presented first, starting with what economists have been calling replication since the early eighties to end with what is now called reproducible research in computational data analysis oriented fields like statistics and signal processing. Since efficient tools are instrumental for a routine implementation of these approaches, a description of some of the available ones is presented next. A toy example demonstrates then the use of two open source software for reproducible data analysis: the ''Sweave family'' and the org-mode of emacs. The former is bound to R while the latter can be used with R, Matlab, Python and many more ''generalist'' data processing software. Both solutions can be used with Unix-like, Windows and Mac families of operating systems. It is argued that neuroscientists could communicate much more efficiently their results by adopting the reproducible research paradigm from their lab books all the way to their articles, thesis and books

A very simple and fast way to access and validate algorithms in reproducible research

The reproducibility of research in bioinformatics refers to the notion that new methodologies/ algorithms and scientific claims have to be published together with their data and source code, in a way that other researchers may verify the findings to further build more knowledge upon them. The replication and corroboration of research results are key to the scientific process and many journals are discussing the matter nowadays, taking concrete steps in this direction. In this journal itself, a very recent opinion note has appeared highlighting the increasing importance of this topic in bioinformatics and computational biology, inviting the community to further discuss the matter. In agreement with that article, we would like to propose here another step into that direction with a tool that allows the automatic generation of a web interface, named web-demo, directly from source code in a very simple and straightforward way. We believe this contribution can help make research not only reproducible but also more easily accessible. A web-demo associated to a published paper can accelerate an algorithm validation with real data, wide-spreading its use with just a few clicks.Fil: Stegmayer, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Pividori, Milton Damián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentin

SOUND SOFTWARE: TOWARDS SOFTWARE REUSE IN AUDIO AND MUSIC RESEARCH

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Quantitative pinch stimulator for exploring evoked nociceptive responses: A pilot study

<p>Abstract</p> <p>Background</p> <p>A mechanical noxious stimulator is useful for studies of pain, both for clinic and basic research. We propose to use a pinch stimulator that can not only generate a quantitative, reproducible noxious pinch but also simultaneously provide a synchronous external trigger signal, which is essential for acquisition of evoked potentials.</p> <p>Methods</p> <p>For ethical considerations, audible and visual aids were incorporated so that pinch force could be regulated within a predetermined level. Reproducibility of the nociceptive responses evoked by this device was validated. The device was constructed with a simple circuit, and the element build-in was delicately selected for the minimum required to produce evoked potentials.</p> <p>Results</p> <p>The magnitude of the force output is linearly proportional to the volts produced by the device (i.e., during the pinch). Increases in force correspond to increases in the number of action potentials induced.</p> <p>Conclusions</p> <p>This device may be useful for studying the mechanisms of nociceptive signal processing in the brain through application of reproducible, noxious pinch stimuli.</p