A Review in Advanced Digital Signal Processing Systems
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32797
A Review in Advanced Digital Signal Processing Systems

Authors: Roza Dastres, Mohsen Soori

Abstract:

Digital Signal Processing (DSP) is the use of digital processing systems by computers in order to perform a variety of signal processing operations. It is the mathematical manipulation of a digital signal's numerical values in order to increase quality as well as effects of signals. DSP can include linear or nonlinear operators in order to process and analyze the input signals. The nonlinear DSP processing is closely related to nonlinear system detection and can be implemented in time, frequency and space-time domains. Applications of the DSP can be presented as control systems, digital image processing, biomedical engineering, speech recognition systems, industrial engineering, health care systems, radar signal processing and telecommunication systems. In this study, advanced methods and different applications of DSP are reviewed in order to move forward the interesting research filed.

Keywords: Digital signal processing, advanced telecommunication, nonlinear signal processing, speech recognition systems.

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References:


[1] J. Xin, and J. E. Esser, “Continuous and Discrete Signals.”
[2] R. Dastres, and M. Soori, “Impact of Meltdown and Spectre on CPU Manufacture Security Issues.” International Journal of Engineering and Future Technology, vol. 18 (2), pp. 62-69, 2020.
[3] R. Dastres, and M. Soori, “A Review in Recent Development of Network Threats and Security Measures.” International Journal of Computer and Information Engineering, vol. 15 (1), pp. 75-81, 2021.
[4] R. Dastres, and M. Soori, “Advanced Image Processing Systems.” International Journal of Imaging and Robotics, vol. 21 (1), pp., 2021.
[5] R. Dastres, and M. Soori, “Secure Socket Layer in the Network and Web Security.” International Journal of Computer and Information Engineering, vol. 14 (10), pp. 330-333, 2020.
[6] R. G. Lyons, and D. L. Fugal, The essential guide to digital signal processing. Pearson Education, 2014.
[7] A. V. Oppenheim, “Applications of digital signal processing.” Englewood Cliffs, vol. pp., 1978.
[8] R. D. Hippenstiel, Detection theory: applications and digital signal processing. CRC Press, 2017.
[9] A. Ortega, P. Frossard, J. Kovačević, J. M. Moura, and P. Vandergheynst, “Graph signal processing: Overview, challenges, and applications.” Proceedings of the IEEE, vol. 106 (5), pp. 808-828, 2018.
[10] P. Crovetti, F. Musolino, O. Aiello, P. Toledo, and R. Rubino, “Breaking the boundaries between analogue and digital.” Electronics Letters, vol. 55 (12), pp. 672-673, 2019.
[11] Y. Tsividis, “Continuous-time digital signal processing.” Electronics Letters, vol. 39 (21), pp. 1, 2003.
[12] N. Ponomareva, O. Ponomareva, and V. Khvorenkov, “Anharmonic Discrete Signal Envelope Detection with Hilbert Transform in the Frequency Domain.” Intellekt Sist Proizv, vol. 16 (1), pp. 33-40, 2018.
[13] T. Kim, and T. Adali, “Fully complex multi-layer perceptron network for nonlinear signal processing.” Journal of VLSI signal processing systems for signal, image and video technology, vol. 32 (1), pp. 29-43, 2002.
[14] J. Engel, L. Hantrakul, C. Gu, and A. Roberts, “Ddsp: Differentiable digital signal processing.” arXiv preprint arXiv:200104643, vol. pp., 2020.
[15] M. B. Milde, H. Blum, A. Dietmüller, D. Sumislawska, J. Conradt, G. Indiveri, and Y. Sandamirskaya, “Obstacle avoidance and target acquisition for robot navigation using a mixed signal analog/digital neuromorphic processing system.” Frontiers in neurorobotics, vol. 11pp. 28, 2017.
[16] Y. Zhao, Y. H. Hu, and J. Liu, “Random triggering-based sub-Nyquist sampling system for sparse multiband signal.” IEEE Transactions on Instrumentation and Measurement, vol. 66 (7), pp. 1789-1797, 2017.
[17] T. Eugene, and S.-S. Manfred, “Introduction to signal processing: sampled signals.” International Journal of Open Information Technologies, vol. 7 (7), pp., 2019.
[18] E. Ivanichenko, “Digital signals processing using non-linear orthogonal transformation in frequency domain.” Вісник Житомирського державного технологічного університету Серія: Технічні науки, vol. (2 (1)), pp. 116-118, 2017.
[19] I. Gadolina, N. Lisachenko, Y. Svirskiy, and D. Dubin, “The Choice of Sampling Frequency and Optimal Method of Signals Digital Processing in Problems of a Random Loading Process Treating to Assess Durability.” Inorganic Materials, vol. 56 (15), pp. 1551-1558, 2020.
[20] R. R. Serrezuela, A. Chavarro, M. Cardozo, A. G. R. Caicedo, and C. A. Cabrera, “Audio signals processing with digital filters implementation using MyDSP.” ARPN Journal of Engineering and Applied Sciences, vol. 12 (16), pp. 4848-4853, 2017.
[21] A. Antoniou, Digital filters: analysis, design, and signal processing applications. McGraw-Hill Education, 2018.
[22] J. L. Rojo-Álvarez, M. Martínez-Ramón, J. M. Marí, and G. Camps-Valls, Digital signal processing with Kernel methods. Wiley Online Library, 2018.
[23] Digital Signal Processing. https://www.rs-online.com/designspark/getting-into-digital-signal-processing-a-basic-introduction.
[24] Y. Salathé, P. Kurpiers, T. Karg, C. Lang, C. K. Andersen, A. Akin, S. Krinner, C. Eichler, and A. Wallraff, “Low-latency digital signal processing for feedback and feedforward in quantum computing and communication.” Physical Review Applied, vol. 9 (3), pp. 034011, 2018.
[25] F. Prieur, O. M. H. Rindal, and A. Austeng, “Signal coherence and image amplitude with the filtered delay multiply and sum beamformer.” IEEE transactions on ultrasonics, ferroelectrics, and frequency control, vol. 65 (7), pp. 1133-1140, 2018.
[26] S. Smith, Digital signal processing: a practical guide for engineers and scientists. Elsevier, 2013.
[27] S. Santra, S. Bhowmick, A. Paul, P. Chatterjee, and A. Deyasi “Development of GUI for text-to-speech recognition using natural language processing,“ In: 2018 2nd International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech). IEEE, pp. 1-4, 2018.
[28] R. Haeb-Umbach, S. Watanabe, T. Nakatani, M. Bacchiani, B. Hoffmeister, M. L. Seltzer, H. Zen, and M. Souden, “Speech processing for digital home assistants: Combining signal processing with deep-learning techniques.” IEEE Signal processing magazine, vol. 36 (6), pp. 111-124, 2019.
[29] A. Y. Tychkov, A. Alimuradov, and P. Churakov, “Adaptive signal processing method for speech organ diagnostics.” Measurement techniques, vol. 59 (5), pp. 485-490, 2016.
[30] Y. Yao, H. Wang, S. Li, Z. Liu, G. Gui, Y. Dan, and J. Hu, “End-to-end convolutional neural network model for gear fault diagnosis based on sound signals.” Applied Sciences, vol. 8 (9), pp. 1584, 2018.
[31] P. Podder, M. Hasan, M. Islam, and M. Sayeed, “Design and implementation of Butterworth, Chebyshev-I and elliptic filter for speech signal analysis.” arXiv preprint arXiv:200203130, vol. pp., 2020.
[32] M. He, Y. Nian, and Y. Gong, “Novel signal processing method for vital sign monitoring using FMCW radar.” Biomedical Signal Processing and Control, vol. 33pp. 335-345, 2017.
[33] K. Lenfors, and A. Nykvist, “Embedded hardware/software co-design methodologies for radar signal processing on multiprocessor system-on-chip.” vol. pp., 2019.
[34] M. K. Kopae, J. E. Prilepsky, S. T. Le, and S. K. Turitsyn “Optical communication based on the periodic nonlinear Fourier transform signal processing,“ In: 2016 IEEE 6th International Conference on Photonics (ICP). IEEE, pp. 1-3, 2016.
[35] N. Chávez, and C. Guillén, “Radar detection in the moments space of the scattered signal parameters.” Digital Signal Processing, vol. 83pp. 359-366, 2018.
[36] J. Le Kernec, F. Fioranelli, C. Ding, H. Zhao, L. Sun, H. Hong, J. Lorandel, and O. Romain, “Radar Signal Processing for Sensing in Assisted Living: The challenges associated with real-time implementation of emerging algorithms.” IEEE Signal Processing Magazine, vol. 36 (4), pp. 29-41, 2019.
[37] H. C. Kumawat, and A. B. Raj “Data acquisition and signal processing system for CW radar,“ In: 2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA). IEEE, pp. 1-5, 2019.
[38] W.-J. Zhu, K.-J. Xu, M. Fang, Z.-W. Shen, and L. Tian, “Variable ratio threshold and zero-crossing detection based signal processing method for ultrasonic gas flow meter.” Measurement, vol. 103pp. 343-352, 2017.
[39] E. E. Franco, and F. Buiochi, “Ultrasonic measurement of viscosity: Signal processing methodologies.” Ultrasonics, vol. 91pp. 213-219, 2019.
[40] Y. Shrivastava, and B. Singh, “Stable cutting zone prediction in CNC turning using adaptive signal processing technique merged with artificial neural network and multi-objective genetic algorithm.” European Journal of Mechanics-A/Solids, vol. 70pp. 238-248, 2018.
[41] X. He, J.-P. Montillet, R. Fernandes, M. Bos, K. Yu, X. Hua, and W. Jiang, “Review of current GPS methodologies for producing accurate time series and their error sources.” Journal of Geodynamics, vol. 106pp. 12-29, 2017.
[42] S. Kolouri, S. R. Park, M. Thorpe, D. Slepcev, and G. K. Rohde, “Optimal mass transport: Signal processing and machine-learning applications.” IEEE signal processing magazine, vol. 34 (4), pp. 43-59, 2017.
[43] J. Hurst, M. Behn, U. Tapken, and L. Enghardt “Sound power measurements at radial compressors using compressed sensing based signal processing methods,“ In: Turbo Expo: Power for Land, Sea, and Air. American Society of Mechanical Engineers, p V02BT43A003, 2019.
[44] E. Wangkanklang, F. Keita, K. Yamaguchi, A. Yoshida, Y. Koike, M. Okage, S. Ishii, and M. Nakamura “The Progress Investigation of Ishikawa Mixing and Grinding Machine Using Sound Signal Processing,“ In: 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE). IEEE, pp. 513-514, 2018.
[45] Y. Wang, N. Liu, H. Guo, and X. Wang, “An engine-fault-diagnosis system based on sound intensity analysis and wavelet packet pre-processing neural network.” Engineering Applications of Artificial Intelligence, vol. 94pp. 103765, 2020.
[46] M. R. Ganji, A. Ghelmani, A. Golroo, and H. Sheikhzadeh, “A Brief Review on the Application of Sound in Pavement Monitoring and Comparison of Tire/Road Noise Processing Methods for Pavement Macrotexture Assessment.” Archives of Computational Methods in Engineering, vol. pp. 1-24, 2020.
[47] G. Allwood, X. Du, K. M. Webberley, A. Osseiran, and B. J. Marshall, “Advances in acoustic signal processing techniques for enhanced bowel sound analysis.” IEEE reviews in biomedical engineering, vol. 12pp. 240-253, 2018.
[48] F. Firuzbakht, A. Fallah, S. Rashidi, and E. R. Khoshnood “Abnormal Heart Sound Diagnosis based on Phonocardiogram Signal Processing,“ In: Electrical Engineering (ICEE), Iranian Conference on. IEEE, pp. 1450-1455, 2018.
[49] M. Hamidi, H. Ghassemian, and M. Imani, “Classification of heart sound signal using curve fitting and fractal dimension.” Biomedical Signal Processing and Control, vol. 39pp. 351-359, 2018.
[50] Y. Yang, and Y. Yue, “English speech sound improvement system based on deep learning from signal processing to semantic recognition.” International Journal of Speech Technology, vol. 23 (3), pp. 505-515, 2020.
[51] H. Takada, T. Ogawa, and H. Matsumoto “Blind signal separation for heart sound and lung sound from auscultatory sound based on the high order statistics,“ In: 2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS). IEEE, pp. 201-205, 2017.
[52] G.-Y. Son, and S. Kwon, “Classification of heart sound signal using multiple features.” Applied Sciences, vol. 8 (12), pp. 2344, 2018.