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"Uses MATLAB[registered] as a computing tool to explore traditional DSP topics and solve problems to gain insight. In this title, practical examples are discussed and useful problems are explored."

"This textbook provides engineering students with instruction on processing signals encountered in speech, music, and wireless communications using software or hardware by employing basic mathematical methods. The book starts with an overview of signal processing, introducing readers to the field. It goes on to give instruction in converting continuous time signals into digital signals and discusses various methods to process the digital signals, such as filtering. The author uses MATLAB throughout as a user-friendly software tool to perform various digital signal processing algorithms and to simulate real-time systems. Readers learn how to convert analog signals into digital signals; how to process these signals using software or hardware; and how to write algorithms to perform useful operations on the acquired signals such as filtering, detecting digitally modulated signals, correcting channel distortions, etc. Students are also shown how to convert MATLAB codes into firmware codes. Further, students will be able to apply the basic digital signal processing techniques in their workplace. The book is based on the author's popular online course at University of California, San Diego."

"This textbook provides engineering students with instruction on processing signals encountered in speech, music, and wireless communications using software or hardware by employing basic mathematical methods. The book starts with an overview of signal processing, introducing readers to the field. It goes on to give instruction in converting continuous time signals into digital signals and discusses various methods to process the digital signals, such as filtering. The author uses MATLAB throughout as a user-friendly software tool to perform various digital signal processing algorithms and to simulate real-time systems. Readers learn how to convert analog signals into digital signals; how to process these signals using software or hardware; and how to write algorithms to perform useful operations on the acquired signals such as filtering, detecting digitally modulated signals, correcting channel distortions, etc. Students are also shown how to convert MATLAB codes into firmware codes. Further, students will be able to apply the basic digital signal processing techniques in their workplace. The book is based on the author's popular online course at University of California, San Diego."

"This book offers a comprehensive introduction to advanced methods for image and video analysis and processing. It covers deraining, dehazing, inpainting, fusion, watermarking and stitching. It describes techniques for face and lip recognition, facial expression recognition, lip reading in videos, moving object tracking, dynamic scene classification, among others.The book combines the latest machine learning methods with computer vision applications, covering topics such as event recognition based on deep learning，dynamic scene classification based on topic model, person re-identification based on metric learning and behavior analysis. It also offers a systematic introduction to image evaluation criteria showing how to use them in different experimental contexts.The book offers an example-based practical guide to researchers, professionals and graduate students dealing with advanced problems in image analysis and computer vision."

"This book highlights new methods, algorithms and software for the digital processing and recovery of signals. In addition, it describes a new method for modeling one dimensional and multidimensional signals as successions of local polynomial splines and their spectral characteristics. It provides examples of how the proposed methods can be applied in specific cases, together with signal processing software examples in the MATLAB environment, and models of special processes in the Simulink environment. The books goal is to make it easier for beginners to understand the subject matter; it is intended for engineers, undergraduate and graduate students engaged in research or the evaluation and design of hardware and software for the digital processing and recovery of signals."

"Metode magnetotellurik adalah salah satu metode geofisika yang digunakan untuk memetakan resitivitas batuan di bawah permukaan bumi. Metode ini biasa digunakan pada daerah prospek panas bumi. Di tengah penggunaannya yang massive di Indonesia, keberadaan software pengolahan data MT masih terbatas pada software yang dikeluarkan oleh produsen alat MT itu sendiri. Penulis berupaya mengembangkan software untuk mengolah data MT berbasis MATLAB. Penelitian yang penulis lakukan difokuskan pada metode seleksi data parsial (crosspower) yang merupakan bagian dari metode statistik yang digunakan untuk menghilangkan data yang menyimpang. Untuk mendapatkan pengukuran berulang, data MT pada domain waktu dibagi kedalam sejumlah segmen. Setiap segmen di asumsikan sebagai satu kali pengukuran. Dari sejumlah segmen tersebut, kemudian dilakukan regresi linier sehingga menghasilkan satu nilai impedansi. Data crosspower adalah data parsial yang diperoleh dari pengolahan langsung setiap segmen sehingga menghasilkan satu nilai respon untuk setiap segmen tersebut. Setelah dilakukan seleksi crosspower, penulis melakukan perbandingan antara data yang dihasilkan oleh pengolahan menggunakan program berbasis MATLAB dengan data hasil seleksi program komersil MTEditor. Hasil inversi dari kedua program tersebut memiliki kesesuaian. Nilai kesalahan relatif terhadap kurva yang dihasilkan MTEditor, turun dari 67.04% menjadi 40.35% setelah dilakukan seleksi. Kurva hasil seleksi memiliki trend yang lebih jelas dan bentuk yang lebih baik.

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Magnetotelluric method is one of geophysical method used to map the subsurface resistivity. This method is often used for geothermal prospecting. Magnetotelluric has been widely used in Indonesia. However, the presence of MT data processing is limited. In this work, we develop software to process MT data base on MATLAB. This research is focused on the method to select partial data (crosspower) involving statistical method to remove the outlier. Time domain MT data is divided in to segments to get a number of measurements. One segment is assumed as one measurement. From these segments, we can perform linear regression that produced one value of impedance.

Crosspower data is the partial MT data obtained by direct process from each segment. Comparison is carry out to the data obtained by this software and MTEditor. Inversion results from both softwares are similar to each other. The relative error compared with MTEditor curve is decrease after selection process. The mean literature error before crosspower selection is 64.04%, and become 40.35 % after selection. Trend and shape of the curve are also getting better. I believe that our finding may be used in science and exploration worlds."