Synthesis Lectures on Algorithms and Software in Engineering – serie

While it may be attractive to view sensors as simple transducers which convert physical quantities into electrical signals, the truth of the matter is more complex. The engineer should have a proper understanding of the physics involved in the conversion process, including interactions with other measurable quantities. A deep understanding of these interactions can be leveraged to apply sensor fusion techniques to minimize noise and/or extract additional information from sensor signals.Advances in microcontroller and MEMS manufacturing, along with improved internet connectivity, have enabled cost-effective wearable and Internet of Things sensor applications. At the same time, machine learning techniques have gone mainstream, so that those same applications can now be more intelligent than ever before. This book explores these topics in the context of a small set of sensor types.We provide some basic understanding of sensor operation for accelerometers, magnetometers,gyroscopes, and pressure sensors. We show how information from these can be fused to provide estimates of orientation. Then we explore the topics of machine learning and sensor data analytics.

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

One such prominent statistical signal processing technique is blind signal separation (BSS). 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

Orthogonal Frequency Division Multiplexing (OFDM) systems are widely used in the standards for digital audio/video broadcasting, WiFi and WiMax. Table of Contents: Introduction / Modeling Wireless Channels / Baseband OFDM System / Carrier Frequency Offset / Peak to Average Power Ratio / Simulation of the Performance of OFDM Systems / Conclusions

This book describes several modules of the Code Excited Linear Prediction (CELP) algorithm. Link to MATLAB® code found within the book Table of Contents: Introduction to Linear Predictive Coding / Autocorrelation Analysis and Linear Prediction / Line Spectral Frequency Computation / Spectral Distortion / The Codebook Search / The FS-1016 Decoder

Table of Contents: Introduction / Radar Waveform Design / Target Tracking with a Particle Filter / Single Target tracking with LFM and CAZAC Sequences / Multiple Target Tracking / Conclusions

From the early pulse code modulation-based coders to some of the recent multi-rate wideband speech coding standards, the area of speech coding made several significant strides with an objective to attain high quality of speech at the lowest possible bit rate.

Gaussian quadrature is a powerful technique for numerical integration that falls under the broad category of spectral methods. Table of Contents: Introduction / Approximating with Polynomials and Related Functions / Gaussian Quadrature / Applications / Links to Mathematical Software

The MPEG-1 Layer III (MP3) algorithm is one of the most successful audio formats for consumer audio storage and for transfer and playback of music on digital audio players. Table of Contents: Introduction / Analysis Subband Filter Bank / Psychoacoustic Model II / MDCT / Bit Allocation, Quantization and Coding / Decoder

Table of Contents: Radar Systems: A Signal Processing Perspective / Introduction to Sparse Representations / Dimensionality Reduction / Radar Signal Processing Fundamentals / Sparse Representations in Radar

Motion estimation is a long-standing cornerstone of image and video processing. Control grid motion estimators based on optical flow can accomplish motion estimation with flexibility similar to pure optical flow, but at a fraction of the computational expense.

Bandwidth extension of speech is used in the International Telecommunication Union G.729.1 standard in which the narrowband bitstream is combined with quantized high-band parameters.

Table of Contents: List of Tables / Preface / Acknowledgments / Delta Quaternion Extended Kalman Filter / Multiple Model Delta Quaternion Filter / Interpolation Volume Calibration / Conclusion / References / Authors' Biographies

It is well known that speckle is a multiplicative noise that degrades image and video quality and the visual expert's evaluation in ultrasound imaging and video. This necessitates the need for robust despeckling image and video techniques for both routine clinical practice and tele-consultation. The goal for this book (book 1 of 2 books) is to introduce the problem of speckle occurring in ultrasound image and video as well as the theoretical background (equations), the algorithmic steps, and the MATLABTM code for the following group of despeckle filters: linear filtering, nonlinear filtering, anisotropic diffusion filtering, and wavelet filtering. This book proposes a comparative evaluation framework of these despeckle filters based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts. Despeckle noise reduction through the application of these filters will improve the visual observation quality or it may be used as a pre-processing step for further automated analysis, such as image and video segmentation, and texture characterization in ultrasound cardiovascular imaging, as well as in bandwidth reduction in ultrasound video transmission for telemedicine applications. The aforementioned topics will be covered in detail in the companion book to this one. Furthermore, in order to facilitate further applications we have developed in MATLABTM two different toolboxes that integrate image (IDF) and video (VDF) despeckle filtering, texture analysis, and image and video quality evaluation metrics. The code for these toolsets is open source and these are available to download complementary to the two books. Table of Contents: Preface / Acknowledgments / List of Symbols / List of Abbreviations / Introduction to Speckle Noise in Ultrasound Imaging and Video / Basics of Evaluation Methodology / Linear Despeckle Filtering / Nonlinear Despeckle Filtering / Diffusion Despeckle Filtering / Wavelet Despeckle Filtering / Evaluation of Despeckle Filtering / Summary and Future Directions / References / Authors' Biographies

In ultrasound imaging and video visual perception is hindered by speckle multiplicative noise that degrades the quality. Noise reduction is therefore essential for improving the visual observation quality or as a pre-processing step for further automated analysis, such as image/video segmentation, texture analysis and encoding in ultrasound imaging and video. The goal of the first book (book 1 of 2 books) was to introduce the problem of speckle in ultrasound image and video as well as the theoretical background, algorithmic steps, and the MatlabTM for the following group of despeckle filters: linear despeckle filtering, non-linear despeckle filtering, diffusion despeckle filtering, and wavelet despeckle filtering. The goal of this book (book 2 of 2 books) is to demonstrate the use of a comparative evaluation framework based on these despeckle filters (introduced on book 1) on cardiovascular ultrasound image and video processing and analysis. More specifically, the despeckle filtering evaluation framework is based on texture analysis, image quality evaluation metrics, and visual evaluation by experts. This framework is applied in cardiovascular ultrasound image/video processing on the tasks of segmentation and structural measurements, texture analysis for differentiating between two classes (i.e. normal vs disease) and for efficient encoding for mobile applications. It is shown that despeckle noise reduction improved segmentation and measurement (of tissue structure investigated), increased the texture feature distance between normal and abnormal tissue, improved image/video quality evaluation and perception and produced significantly lower bitrates in video encoding. Furthermore, in order to facilitate further applications we have developed in MATLABTM two different toolboxes that integrate image (IDF) and video (VDF) despeckle filtering, texture analysis, and image and video quality evaluation metrics. The code for these toolsets is open source and these are available to download complementary to the two monographs.

The availability of inexpensive, custom, highly integrated circuits is enabling some very powerful systems that bring together sensors, smart phones, wearables, cloud computing, and other technologies. To design these types of complex systems we are advocating a top-down simulation methodology to identify problems early. This approach enables software development to start prior to expensive chip and hardware development. We call the overall approach virtual design. This book explains why simulation has become important for chip design and provides an introduction to some of the simulation methods used. The audio lifelogging research project demonstrates the virtual design process in practice. The goals of this book are to: explain how silicon design has become more closely involved with system design;show how virtual design enables top down design;explain the utility of simulation at different abstraction levels;show how open source simulation software was used in audio lifelogging. The target audience for this book are faculty, engineers, and students who are interested in developing digital devices for Internet of Things (IoT) types of products.

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 where multiple users can build their own sensing applications at the same time.

The adaptive configuration of nodes in a sensor network has the potential to improve sequential estimation performance by intelligently allocating limited sensor network resources.

Additionally, in trending applications like augmented and virtual reality usually, blur is introduced in order to provide/enhance depth perception.Digital images and videos are produced every day in astonishing amounts and the demand for higher quality is constantly rising which creates a need for advanced image quality assessment.