Pub Date : 2021-07-06DOI: 10.2200/s01106ed1v01y202105ase021
Scott A. Whitmire
Abstract Software development is hard, but creating good software is even harder, especially if your main job is something other than developing software. Engineer Your Software! opens the world of...
{"title":"Engineer Your Software!","authors":"Scott A. Whitmire","doi":"10.2200/s01106ed1v01y202105ase021","DOIUrl":"https://doi.org/10.2200/s01106ed1v01y202105ase021","url":null,"abstract":"Abstract Software development is hard, but creating good software is even harder, especially if your main job is something other than developing software. Engineer Your Software! opens the world of...","PeriodicalId":303988,"journal":{"name":"Synthesis Lectures on Algorithms and Software in Engineering","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126347561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-05DOI: 10.2200/s01065ed1v01y202012ase020
J. Andrade
{"title":"A Survey of Blur Detection and Sharpness Assessment Methods","authors":"J. Andrade","doi":"10.2200/s01065ed1v01y202012ase020","DOIUrl":"https://doi.org/10.2200/s01065ed1v01y202012ase020","url":null,"abstract":"","PeriodicalId":303988,"journal":{"name":"Synthesis Lectures on Algorithms and Software in Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131544123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-12DOI: 10.2200/s00951ed1v01y201908ase019
I. Kyriakides
Abstract The adaptive configuration of nodes in a sensor network has the potential to improve sequential estimation performance by intelligently allocating limited sensor network resources. In addi...
传感器网络中节点的自适应配置可以通过智能地分配有限的传感器网络资源来提高序列估计的性能。另外…
{"title":"Cognitive Fusion for Target Tracking","authors":"I. Kyriakides","doi":"10.2200/s00951ed1v01y201908ase019","DOIUrl":"https://doi.org/10.2200/s00951ed1v01y201908ase019","url":null,"abstract":"Abstract The adaptive configuration of nodes in a sensor network has the potential to improve sequential estimation performance by intelligently allocating limited sensor network resources. In addi...","PeriodicalId":303988,"journal":{"name":"Synthesis Lectures on Algorithms and Software in Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121224692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-17DOI: 10.2200/S00886ED1V01Y201811ASE018
Vimal Kumar, Amartya Sen, S. Madria
Abstract The sensor cloud is a new model of computing paradigm for Wireless Sensor Networks (WSNs), which facilitates resource sharing and provides a platform to integrate different sensor networks...
{"title":"Secure Sensor Cloud","authors":"Vimal Kumar, Amartya Sen, S. Madria","doi":"10.2200/S00886ED1V01Y201811ASE018","DOIUrl":"https://doi.org/10.2200/S00886ED1V01Y201811ASE018","url":null,"abstract":"Abstract The sensor cloud is a new model of computing paradigm for Wireless Sensor Networks (WSNs), which facilitates resource sharing and provides a platform to integrate different sensor networks...","PeriodicalId":303988,"journal":{"name":"Synthesis Lectures on Algorithms and Software in Engineering","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121181804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-02-19DOI: 10.2200/S00258ED1V01Y201003ASE006
Kostas Kokkinakis, P. Loizou
With human-computer interactions and hands-free communications becoming overwhelmingly important in the new millennium, recent research efforts have been increasingly focusing on state-of-the-art multi-microphone signal processing solutions to improve speech intelligibility in adverse environments. One such prominent statistical signal processing technique is blind signal separation (BSS). BSS was first introduced in the early 1990s and quickly emerged as an area of intense research activity showing huge potential in numerous applications. BSS comprises the task of 'blindly' recovering a set of unknown signals, the so-called sources from their observed mixtures, based on very little to almost no prior knowledge about the source characteristics or the mixing structure. The goal of BSS is to process multi-sensory observations of an inaccessible set of signals in a manner that reveals their individual (and original) form, by exploiting the spatial and temporal diversity, readily accessible through a multi-microphone configuration. Proceeding blindly exhibits a number of advantages, since assumptions about the room configuration and the source-to-sensor geometry can be relaxed without affecting overall efficiency. This booklet investigates one of the most commercially attractive applications of BSS, which is the simultaneous recovery of signals inside a reverberant (naturally echoing) environment, using two (or more) microphones. In this paradigm, each microphone captures not only the direct contributions from each source, but also several reflected copies of the original signals at different propagation delays. These recordings are referred to as the convolutive mixtures of the original sources. The goal of this booklet in the lecture series is to provide insight on recent advances in algorithms, which are ideally suited for blind signal separation of convolutive speech mixtures. More importantly, specific emphasis is given in practical applications of the developed BSS algorithms associated with real-life scenarios. The developed algorithms are put in the context of modern DSP devices, such as hearing aids and cochlear implants, where design requirements dictate low power consumption and call for portability and compact size. Along these lines, this booklet focuses on modern BSS algorithms which address (1) the limited amount of processing power and (2) the small number of microphones available to the end-user. Table of Contents: Fundamentals of blind signal separation / Modern blind signal separation algorithms / Application of blind signal processing strategies to noise reduction for the hearing-impaired / Conclusions and future challenges / Bibliography
{"title":"Advances in Modern Blind Signal Separation Algorithms: Theory and Applications","authors":"Kostas Kokkinakis, P. Loizou","doi":"10.2200/S00258ED1V01Y201003ASE006","DOIUrl":"https://doi.org/10.2200/S00258ED1V01Y201003ASE006","url":null,"abstract":"With human-computer interactions and hands-free communications becoming overwhelmingly important in the new millennium, recent research efforts have been increasingly focusing on state-of-the-art multi-microphone signal processing solutions to improve speech intelligibility in adverse environments. One such prominent statistical signal processing technique is blind signal separation (BSS). BSS was first introduced in the early 1990s and quickly emerged as an area of intense research activity showing huge potential in numerous applications. BSS comprises the task of 'blindly' recovering a set of unknown signals, the so-called sources from their observed mixtures, based on very little to almost no prior knowledge about the source characteristics or the mixing structure. The goal of BSS is to process multi-sensory observations of an inaccessible set of signals in a manner that reveals their individual (and original) form, by exploiting the spatial and temporal diversity, readily accessible through a multi-microphone configuration. Proceeding blindly exhibits a number of advantages, since assumptions about the room configuration and the source-to-sensor geometry can be relaxed without affecting overall efficiency. This booklet investigates one of the most commercially attractive applications of BSS, which is the simultaneous recovery of signals inside a reverberant (naturally echoing) environment, using two (or more) microphones. In this paradigm, each microphone captures not only the direct contributions from each source, but also several reflected copies of the original signals at different propagation delays. These recordings are referred to as the convolutive mixtures of the original sources. The goal of this booklet in the lecture series is to provide insight on recent advances in algorithms, which are ideally suited for blind signal separation of convolutive speech mixtures. More importantly, specific emphasis is given in practical applications of the developed BSS algorithms associated with real-life scenarios. The developed algorithms are put in the context of modern DSP devices, such as hearing aids and cochlear implants, where design requirements dictate low power consumption and call for portability and compact size. Along these lines, this booklet focuses on modern BSS algorithms which address (1) the limited amount of processing power and (2) the small number of microphones available to the end-user. Table of Contents: Fundamentals of blind signal separation / Modern blind signal separation algorithms / Application of blind signal processing strategies to noise reduction for the hearing-impaired / Conclusions and future challenges / Bibliography","PeriodicalId":303988,"journal":{"name":"Synthesis Lectures on Algorithms and Software in Engineering","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134475658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-04DOI: 10.2200/S00168ED1V01Y200812ASE002
S. P. Sira, A. Papandreou-Suppappola, D. Morrell
Recent advances in sensor technology and information processing afford a new flexibility in the design of waveforms for agile sensing. Sensors are now developed with the ability to dynamically choose their transmit or receive waveforms in order to optimize an objective cost function. This has exposed a new paradigm of significant performance improvements in active sensing: dynamic waveform adaptation to environment conditions, target structures, or information features. The manuscript provides a review of recent advances in waveform-agile sensing for target tracking applications. A dynamic waveform selection and configuration scheme is developed for two active sensors that track one or multiple mobile targets. A detailed description of two sequential Monte Carlo algorithms for agile tracking are presented, together with relevant Matlab code and simulation studies, to demonstrate the benefits of dynamic waveform adaptation. The work will be of interest not only to practitioners of rada and sonar, but also other applications where waveforms can be dynamically designed, such as communications and biosensing. Table of Contents: Waveform-Agile Target Tracking Application Formulation / Dynamic Waveform Selection with Application to Narrowband and Wideband Environments / Dynamic Waveform Selection for Tracking in Clutter / Conclusions / CRLB Evaluation for Gaussian Envelope GFM Chirp from the Ambiguity Function / CRLB Evaluation from the Complex Envelope
{"title":"Advances in Waveform-Agile Sensing for Tracking","authors":"S. P. Sira, A. Papandreou-Suppappola, D. Morrell","doi":"10.2200/S00168ED1V01Y200812ASE002","DOIUrl":"https://doi.org/10.2200/S00168ED1V01Y200812ASE002","url":null,"abstract":"Recent advances in sensor technology and information processing afford a new flexibility in the design of waveforms for agile sensing. Sensors are now developed with the ability to dynamically choose their transmit or receive waveforms in order to optimize an objective cost function. This has exposed a new paradigm of significant performance improvements in active sensing: dynamic waveform adaptation to environment conditions, target structures, or information features. The manuscript provides a review of recent advances in waveform-agile sensing for target tracking applications. A dynamic waveform selection and configuration scheme is developed for two active sensors that track one or multiple mobile targets. A detailed description of two sequential Monte Carlo algorithms for agile tracking are presented, together with relevant Matlab code and simulation studies, to demonstrate the benefits of dynamic waveform adaptation. The work will be of interest not only to practitioners of rada and sonar, but also other applications where waveforms can be dynamically designed, such as communications and biosensing. Table of Contents: Waveform-Agile Target Tracking Application Formulation / Dynamic Waveform Selection with Application to Narrowband and Wideband Environments / Dynamic Waveform Selection for Tracking in Clutter / Conclusions / CRLB Evaluation for Gaussian Envelope GFM Chirp from the Ambiguity Function / CRLB Evaluation from the Complex Envelope","PeriodicalId":303988,"journal":{"name":"Synthesis Lectures on Algorithms and Software in Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125841469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-07-21DOI: 10.2200/s00116ed1v01y200805ase001
C. Loizou, C. Pattichis
Abstract It is well-known that speckle is a multiplicative noise that degrades image quality and the visual evaluation in ultrasound imaging. This necessitates the need for robust despeckling techniques for both routine clinical practice and teleconsultation. The goal for this book is to introduce the theoretical background (equations), the algorithmic steps, and the MATLAB™ code for the following group of despeckle filters: linear filtering, nonlinear filtering, anisotropic diffusion filtering and wavelet filtering. The book proposes a comparative evaluation framework of these despeckle filters based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts, in the assessment of cardiovascular ultrasound images recorded from the carotid artery. The results of our work presented in this book, suggest that the linear local statistics filter DsFlsmv, gave the best performance, followed by the nonlinear geometric filter DsFgf4d, and the linear homogeneous mask area filte...
{"title":"Despeckle Filtering Algorithms and Software for Ultrasound Imaging","authors":"C. Loizou, C. Pattichis","doi":"10.2200/s00116ed1v01y200805ase001","DOIUrl":"https://doi.org/10.2200/s00116ed1v01y200805ase001","url":null,"abstract":"Abstract It is well-known that speckle is a multiplicative noise that degrades image quality and the visual evaluation in ultrasound imaging. This necessitates the need for robust despeckling techniques for both routine clinical practice and teleconsultation. The goal for this book is to introduce the theoretical background (equations), the algorithmic steps, and the MATLAB™ code for the following group of despeckle filters: linear filtering, nonlinear filtering, anisotropic diffusion filtering and wavelet filtering. The book proposes a comparative evaluation framework of these despeckle filters based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts, in the assessment of cardiovascular ultrasound images recorded from the carotid artery. The results of our work presented in this book, suggest that the linear local statistics filter DsFlsmv, gave the best performance, followed by the nonlinear geometric filter DsFgf4d, and the linear homogeneous mask area filte...","PeriodicalId":303988,"journal":{"name":"Synthesis Lectures on Algorithms and Software in Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128941657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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