Surampudi Srinivasa Rao

@mrcet.ac.in

Professor, Electronics and Communication Engineering
Malla Reddy College of Engineering and Technology

Surampudi Srinivasa Rao


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https://researchid.co/drsurampudi
Dr S SRINIVASA RAO
B.TECH, M.TECH, , MIEEE, MISTE, MIETE
Professor & Principal

“EDUCATION IS THE ARCHITECTURE OF THE SOUL”
Dr S Srinivasa Rao, Principal, Malla Reddy College of Engineering and Technology have an experience of more than 30 years in Teaching and Research put together. He did his B.Tech from one of the prestigious colleges in India, Madras Institute of Technology, Chennai, M.Tech and PhD from JNTUH, Hyderabad. He has published more than 50+ research papers in various National and International Journals. He has more than 10 National and 1 International Patents. He is the visiting Professor for LUC, Malaysia. He is the recipient of BEST TEACHER AWARD; BEST PRINCIPAL AWARD and HONORARY FELLOWSHIP FOR VISIONARY EDUCATIONAL LEADERSHIP AWARD. He is the member of IEEE, ISTE and IETE. Under his supervision 5 research scholars received their PhD Degree and 6 students are working under his supervision. Areas of Interest include Wireless Communications, SDR..

EDUCATION

PhD: 2013, Wireless Communications, JNTUH Hyderabad.
M.Tech-2004, DSCE, JNTU College of Engineering Hyderabad, JNTUH Hyderabad.
B.Tech-1989, ECE, Madras Institute of Technology, Anna University, Chennai.

RESEARCH, TEACHING, or OTHER INTERESTS

Electrical and Electronic Engineering, Multidisciplinary, Artificial Intelligence, Computer Networks and Communications
29

Scopus Publications

96

Scholar Citations

6

Scholar h-index

5

Scholar i10-index

Scopus Publications

  • Multi-stage decimation with hybrid CIC-polyphase filtering for IoT gateway sample rate conversion
    Swetha Pinjerla, Surampudi Srinivasa Rao, P Chandrasekhar Reddy
    Scientific Reports, 2026
    In real-time digital signal processing, the multirate transformation is a commonly used technique for interpolation and decimation. Comb-based decimation filters are used in wireless applications because of their minimal complexity and effective alias suppression. One symmetrical Finite Impulse Response (FIR) filter that may be used as a decimation filter is the cascaded integrator-comb (CIC) filter. Compared to other decimation filters, the CIC filter operates faster and uses less hardware because it does not require multipliers. Efficient digital filtering is critical in modern wireless communication systems, where real-time processing and resource optimization are essential. This paper presents a multi-stage hybrid polyphase CIC filter architecture implemented on a Xilinx Virtex-4 Field-Programmable Gate Array (FPGA) to enhance signal processing performance. The proposed method integrates a polyphase CIC filter with an FIR compensation filter, addressing the passband droop and improving frequency response. By leveraging polyphase decomposition and pipeline optimization, the design reduces computational complexity while maintaining high accuracy. The FPGA-based implementation ensures low latency, high throughput, and efficient hardware utilization, making it ideal for high-speed wireless applications. Experimental results demonstrate that the proposed filter achieves superior filtering performance compared to conventional CIC filters, offering a robust solution for real-time digital signal processing. The proposed method achieves substantial hardware savings, utilizing only 289 Slice Registers, 25 LUTs, 346 Flip-Flops, 63 BRAMs, and 76 DSPs, compared to the highest values from prior works, which consumed up to 628 Registers, 442 LUTs, 654 BRAMs, and 364 DSPs. This represents a reduction of up to 54% in Slice Registers, 94% in LUTs, and 88% in DSPs, highlighting the efficiency of the proposed architecture for SDR-based IoT gateways.
  • Area and Power Optimized Architecture of Sample Rate Converter for IoT Gateway Applications
    Swetha Pinjerla, Surampudi Srinivasa Rao, Puttha Chandrasekhar Reddy
    International Journal of Electrical and Computer Engineering Systems, 2026
    Nowadays, the Internet of things plays a major role in society for various applications such as medical diagnostics, telecommunications, agriculture, mobile computing, broadcasting, video surveillance etc. In Internet of Things (IoT) networks, several sensors with different data rates should be integrated to perform overall control or monitoring processes.High-speed data transmission technologies should be needed to communicate with IoT servers or storage. Generally, a gateway device is used to integrate low-data rate devices and IoT interfaces. Field Programmable Gate Array Logic (FPGA) can be utilized to implement high-speed and low-power gateway. The paper suggests a design of an FPGA-based IoT gateway architecture, which allows multi-protocol communications and an effective way of controlling sample rates. The design provides RF transceivers, protocol specific modules, and dynamic Sample Rate (SR) Selector to support smooth synchronization of data between diverse IoT devices. Clock generation and control blocks guarantee adaptive frequency assignment and upsampling and downsampling CIC filtering-based units ensure good signal conditioning. Experimental analysis shows that the presented method creates the low root mean square error (RMSE): 1.2 percent (downlink) and 1.4 percent (uplink), and high signal to noise ratios (SNR): 26.3 dB (downlink) and 24.8 dB (uplink) in 45 nm CMOS technology, resulting in better results than conventional 180 nm implementations. The Application-Specific Integrated Circuit (ASIC) implementation achieved a compact core area, reducing from 2.3 μm2 at 180 nm to 0.3 μm2 at 45 nm, demonstrating significant area efficiency with technology scaling. The results affirm that the architecture can provide reliable and high-quality data transfers of next-generation IoT gateways.
  • Dynamic Cyber Attack Detection and Spyware Identification Using Deep Learning Methods
    A. Anuradha, Arun Singh Chohan, S. Srinivasa Rao
    Lecture Notes in Networks and Systems, 2025
  • Retraction Note: Hybrid Speech Steganography System using SS-RDWT with IPDP-MLE approach (Soft Computing, (2023), 27, 2, (1117-1129), 10.1007/s00500-021-05970-4)
    R. Chinna Rao, P. V. Y. Jayasree, S. Srinivasa Rao
    Soft Computing, 2024
  • Automatic Semantic Segmentation and Classification of Remote Sensing Image Data for Flood Detection Using Novel LSTM Neural Network
    Amruta Sonavale, Midhun Chakkaravarthy, Surampudi Srinivasa Rao, Hishamuddin Bin M. Salleh, Jagannath Jadhav
    SN Computer Science, 2024
  • Design of energy efficient and reconfigurable sample rate converter using FPGA devices
    Swetha Pinjerla, Surampudi Srinivasa Rao, Puttha Chandrasekhar Reddy
    Indonesian Journal of Electrical Engineering and Computer Science, 2024
    <p>The technique of sampling rate conversion is frequently employed in various fields. A discrete time-varying filter, as well as a sample skip or sample duplicate operation, are required for the most general instance of an irrational and time-variable conversion factor. A wide band of signals is employed in a communication system, especially in specific situations where data must be transferred directly. A broadband sample rate converter with changeable filter parameters is necessary in such cases. Sample rate conversion is a communication system technology that accepts a band-limited high sample rate modulated signal and uses filtering to retrieve the original message signal. In this work, an energy-efficient implementation of a reconfigurable field programmable gate arrays (FPGA) architecture for a sample rate converter is proposed. In applications such as multi-rate signal processing and the construction of channelized receivers, sample rate conversion is used. In this work, a new FPGA based design is proposed to perform multiple sample rate conversion for various data transmission protocols such as Wi-Fi, ZigBee and Bluetooth. A lowpass filter with a 2.45 GHz filter with the minimum number of taps is used to avoid the aliasing effect. Xilinx synthesis tools are used to estimate hardware resource utilization and speed analyses. XC6VCX240t-2FF484 FPGA achieves 15% hardware resource occupancy at a maximum clock speed of 133 MHz.</p>
  • Cooperative Spectrum Sensing Performance Assessment using Machine Learning in Cognitive Radio Sensor Networks
    Pallam Venkatapathi, Habibulla Khan, S. Srinivasa Rao, Govardhani Immadi
    Engineering Technology and Applied Science Research, 2024
    The Cognitive Radio (CR) is an imminent technology, intended to make more effective use of the available spectrum by giving access to licensed frequency bands by unlicensed Secondary Users (SUs) without affecting Primary licensed Users (PUs). Depending on the region where the energy is being observed, each CR communicates local decisions or the seen energy to the Fusion Center (FC). This study presents the many plots that discuss an enhanced double threshold through the Cooperative Spectrum Sensing (CSS) approach. The FC then combines local decisions with the measured energy values to reach a final decision. The usage of several machine learning methods in spectrum decision with the myopic decision is estimated. The system seeks to enhance the long-term overall performance of the SU.
  • FLOOD DETECTION BASED ON FEED FORWARD NEURAL NETWORK
    Journal of Environmental Protection and Ecology, 2024
  • Machine Learning Model Comparison for Flood Detection Application from Satellite Images
    Amruta Sonavale, Midhun Chakkaravarthy, Surampudi Srinivasa Rao, Hishamuddin Bin M. Salleh, Jagannath Jadhav
    2nd IEEE International Conference on Data Science and Network Security Icdsns 2024, 2024
    Backgrounds: Flooding, a rapidly increasing and increasingly frequent natural disaster, requires effective management, even if unavoidable, and the development of an effective classifier for image detection is crucial for effective response. Methods: The study uses machine learning methods like closest K-nearest neighbors, logistic regression, support vector classification, and decision tree as classifiers. The accuracy of these algorithms varies. The dataset, consisting of ground and space-based sources, is used to determine their accuracy rates. The most accurate classifier is used for forecasting flooding in advance, allowing for faster evacuation and care for those in need. Result: In this case, we could anticipate the likelihood of flooding by analyzing historical rainfall data. The support vector machine produced an efficient accuracy of 93.92%. Conclusion: The accuracy of each classifier is shown, and detection is performed mostly with great precision. The outcomes of any image tests conducted are shown as well.
  • Multimodal and Multi-Temporal in Satellite Images Based on Flood Detection: A Comparative Study
    Amruta Sonavale, Midhun Chakkaravarthy, Surampudi Srinivasa Rao, Hishamuddin Bin M. Salleh, Jagannath Jadhav
    2nd IEEE International Conference on Data Science and Network Security Icdsns 2024, 2024
    Floods can cause significant damage to human lives and property, necessitating precise post-flood evaluations for rescue efforts. Methods: It explores flood location AI techniques using a multi-modular and multi-fleeting picture dataset, ranging from traditional methods like multi-facet perceptron (MLP), support vector machine (SVM) and Deep convolution neural network (DCNN) to space transformation-based strategies. We utilized SPOT-5 and RADAR pictures from the November 2000 flood in Gloucester, UK. Results: The F1 score of 0.8846 and the region under the accuracy (AUC) bend (PR) of 0.9173 in the examinations were marginally higher than those that used machine strategies and investment of human resources. Conclusion: Utilizing a multi-modular and multi-temporal image dataset looked at a few customary flood location AI techniques as MLP, SVM and DCNN, to later space transformation-based strategies. This enhancement is due to the 20 labelled data samples used in the domain adaptation- based on semi-supervised domain adaptation (SSDA).
  • Peak to Average Power Ratio Reduction for MC FDMA using Companding
    M. Sucharitha, B. Jyothi, S. Srinivasa Rao, K. Mallikarjuna Lingam
    Aip Conference Proceedings, 2023
  • An Efficient Discrete Wavelet Transform Architecture with Low Power and Multiplier-Less Structure for Pervasive Biomedical Image Processing Application
    Maram Anantha Guptha, Surampudi Srinivasa Rao, Ravindrakumar Selvaraj
    Eai Endorsed Transactions on Pervasive Health and Technology, 2023
  • Hybrid Speech Steganography System using SS-RDWT with IPDP-MLE approach
    R. Chinna Rao, P. V. Y. Jayasree, S. Srinivasa Rao
    Soft Computing, 2023
  • A Novel Optimization based Energy Efficient and Secured Routing Scheme using SRFIS-CWOSRR for Wireless Sensor Networks
    S. Srinivasa Rao, K. Chenna Keshava Reddy, S. Ravi Chand
    International Journal of Electrical and Electronics Research, 2022
  • Sampling Rate Conversion Techniques-A Review
    Swetha Pinjerla, Srinivasa Rao S, Chandrasekhar Reddy P
    4th International Conference on Recent Trends in Computer Science and Technology Icrtcst 2021 Proceedings, 2022
  • Clusters-based rendezvousing approach for scheduling the flash crowd transmissions over cognitive radio networks
    Ch. Suneetha, S. Srinivasa Rao, K.S. Ramesh
    International Journal of Ultra Wideband Communications and Systems, 2022
  • Spread Spectrum Based Speech Steganography Using RDWT
    R Chinna Rao, PVY Jayasree, S Srinivasa Rao, Pala Mahesh Kumar
    Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems Icesc 2021, 2021
  • An improved energy efficient, low power nanometer architecture for biomedical image processing application using finfet devices
    Journal of Green Engineering, 2021
  • Convolution Based Multilevel DWT Architecture Using Distributed Arithmetic and FIR Bi-orthogonal Filter for Two-Dimensional Data Analysis
    Maram Anantha Guptha, Surampudi Srinivasa Rao, Ravindrakumar Selvaraj
    Lecture Notes in Electrical Engineering, 2021
  • Early Detection of Dementia Disease Using Data Mining Techniques
    M. Sucharitha, Chinmay Chakraborty, S. Srinivasa Rao, V. S. K. Reddy
    Studies in Big Data, 2021
  • Performance analysis of IPDP protocol enabled vocoders using wire shark for acoustic application
    Journal of Green Engineering, 2020
  • Ideal frequency rendezvousing for multiuser communication (IFRMC) over cognitive radio network
    Ch. Suneetha, S. Srinivasa Rao, K. S. Ramesh
    International Journal of Speech Technology, 2020
  • Performance of threshold detection in cognitive radio with improved otsu’s and recursive one-sided hypothesis testing technique
    Pallam Venkatapathi, Habibulla Khan, Suhasini Subba Rao, M Islam, C Koh, et al.
    International Journal of Innovative Technology and Exploring Engineering, 2019
  • QoS based secondary user selection using swarm optimization techniques in cognitive radio network
    Journal of Critical Reviews, 2019
  • Basic framework of vocoders for speech processing
    R. Chinna Rao, D. Elizabath Rani, S. Srinivasa Rao
    Advances in Intelligent Systems and Computing, 2019
  • Adaptive sampling rate converter for wireless sensor networks
    P. Swetha, S. Srinivasa Rao, P. Chandrasekhar Reddy
    Advances in Intelligent Systems and Computing, 2019
  • Performance enhancement of vocoders using IPDP protocol with DTX algorithm for speech processing in mobile networks
    Journal of Advanced Research in Dynamical and Control Systems, 2019
  • Design of fuzzy logic system for cognitive radio networks for efficient spectrum decision and channel assignment
    International Journal of Engineering and Technology Uae, 2018
  • Notice of Removal: Low power area efficient dynamic quad PCM Codec with filter for communication applications
    T. Vasudeva Reddy, S. Srinivasa Rao, P.V. Sridevi
    International Conference on Electrical Electronics Signals Communication and Optimization Eesco 2015, 2015

RECENT SCHOLAR PUBLICATIONS

  • Multi-stage decimation with hybrid CIC-polyphase filtering for IoT gateway sample rate conversion
    S Pinjerla, SS Rao, PC Reddy
    Scientific Reports , 2025
    2025
    Citations: 1
  • Retraction Note: Hybrid Speech Steganography System using SS-RDWT with IPDP-MLE approach
    RC Rao, PVY Jayasree, SS Rao
    Soft Computing 28 (Suppl 2), 989-989 , 2024
    2024
  • Cooperative spectrum sensing performance assessment using machine learning in cognitive radio sensor networks
    P Venkatapathi, H Khan, SS Rao, G Immadi
    Engineering, Technology & Applied Science Research 14 (1), 12875-12879 , 2024
    2024
    Citations: 14
  • Carboxymethyl cellouse stabilized cobalt sulfide nanoparticles: preparation, characterization and application
    BS Diwakar, D Rajeswari, J Singh, P Haritha, S Srinivasa Rao, ...
    Journal of Cluster Science 34 (5), 2429-2439 , 2023
    2023
    Citations: 12
  • An Efficient Discrete Wavelet Transform Architecture with Low Power and Multiplier-Less Structure for Pervasive Biomedical Image Processing Application.
    MA Guptha, SS Rao, R Selvaraj
    EAI Endorsed Transactions on Pervasive Health & Technology 9 (1) , 2023
    2023
    Citations: 6
  • RETRACTED ARTICLE: Hybrid Speech Steganography System using SS-RDWT with IPDP-MLE approach
    RC Rao, PVY Jayasree, SS Rao
    Soft Computing 27 (2), 1117-1129 , 2023
    2023
    Citations: 4
  • Clusters-based rendezvousing approach for scheduling the flash crowd transmissions over cognitive radio networks
    C Suneetha, SS Rao, KS Ramesh
    International Journal of Ultra Wideband Communications and Systems 5 (1), 1-11 , 2022
    2022
  • Spread Spectrum Based Speech Steganography Using RDWT
    RC Rao, PVY Jayasree, SS Rao, PM Kumar
    2021 Second International Conference on Electronics and Sustainable … , 2021
    2021
    Citations: 2
  • Basic Framework of Different Steganography Techniques for Security Applications
    RC Rao, PVY Jayasree, SS Rao, GS Yeshwanth, KRS Megana, K Shreya, ...
    International Conference on Soft Computing and Signal Processing, 571-583 , 2021
    2021
    Citations: 1
  • An integrated VLSI architecture for forward and backward lifting scheme discrete wavelet transform using FinFET device
    MA Guptha, SS Rao, R Selvaraj
    Soft Computing and Signal Processing: Proceedings of 3rd ICSCSP 2020, Volume … , 2021
    2021
    Citations: 2
  • Convolution based multilevel DWT architecture using distributed arithmetic and FIR bi-orthogonal filter for two-dimensional data analysis
    MA Guptha, S Srinivasa Rao, R Selvaraj
    Advances in Smart Communication and Imaging Systems: Select Proceedings of … , 2021
    2021
    Citations: 1
  • Architecture Using Distributed Arithmetic and FIR Bi-orthogonal Filter for Two-Dimensional Data Analysis
    MA Guptha, SS Rao, R Selvaraj
    Advances in Smart Communication and Imaging Systems: Select Proceedings of … , 2021
    2021
  • Ideal frequency rendezvousing for multiuser communication (IFRMC) over cognitive radio network
    C Suneetha, S Srinivasa Rao, KS Ramesh
    International Journal of Speech Technology 23 (3), 537-547 , 2020
    2020
    Citations: 2
  • Early detection of dementia disease using data mining techniques
    M Sucharitha, C Chakraborty, S Srinivasa Rao, VSK Reddy
    Internet of Things for Healthcare Technologies, 177-194 , 2020
    2020
    Citations: 6
  • Performance Analysis of IPDP Protocol Enabled Vocoders Using Wire Shark for Acoustic Application
    RC Rao, PVY Jayasree, SS Rao
    Journal of Green Engineering 10, 13049-13064 , 2020
    2020
  • Performance analysis of spectrum sensing in cognitive radio under low SNR and noise floor
    P Venkatapathi, H Khan, SS Rao
    International Journal of Engineering and Advanced Technology 9 (2), 2655-2661 , 2019
    2019
    Citations: 11
  • Performance of threshold detection in cognitive radio with improved Otsu’s and recursive one-sided hypothesis testing technique
    P Venkatapathi, H Khan, S SrinivasaRao
    International Journal of Innovative Technology and Exploring Engineering 8 … , 2019
    2019
    Citations: 5
  • Basic Framework of Vocoders for Speech Processing
    RC Rao, D Elizabath Rani, S Srinivasa Rao
    Soft Computing and Signal Processing: Proceedings of ICSCSP 2018, Volume 2 … , 2019
    2019
  • Adaptive Sampling Rate Converter for Wireless Sensor Networks
    P Swetha, S Srinivasa Rao, P Chandrasekhar Reddy
    Soft Computing and Signal Processing: Proceedings of ICSCSP 2018, Volume 1 … , 2019
    2019
    Citations: 1
  • A finite element analysis of initial stresses and displacements in the tooth and the periodontium in periodontally compromised simulations: Labial versus lingual force application
    JB Kumar, GJ Reddy, M Sridhar, TJ Reddy, PJ Reddy, SS Rao
    Journal of Dr. YSR University of Health Sciences 5 (1), 34-43 , 2016
    2016
    Citations: 13

MOST CITED SCHOLAR PUBLICATIONS

  • Cooperative spectrum sensing performance assessment using machine learning in cognitive radio sensor networks
    P Venkatapathi, H Khan, SS Rao, G Immadi
    Engineering, Technology & Applied Science Research 14 (1), 12875-12879 , 2024
    2024
    Citations: 14
  • A finite element analysis of initial stresses and displacements in the tooth and the periodontium in periodontally compromised simulations: Labial versus lingual force application
    JB Kumar, GJ Reddy, M Sridhar, TJ Reddy, PJ Reddy, SS Rao
    Journal of Dr. YSR University of Health Sciences 5 (1), 34-43 , 2016
    2016
    Citations: 13
  • Carboxymethyl cellouse stabilized cobalt sulfide nanoparticles: preparation, characterization and application
    BS Diwakar, D Rajeswari, J Singh, P Haritha, S Srinivasa Rao, ...
    Journal of Cluster Science 34 (5), 2429-2439 , 2023
    2023
    Citations: 12
  • Performance analysis of spectrum sensing in cognitive radio under low SNR and noise floor
    P Venkatapathi, H Khan, SS Rao
    International Journal of Engineering and Advanced Technology 9 (2), 2655-2661 , 2019
    2019
    Citations: 11
  • Human activity tracking using RFID tags
    SS Rao, EG Rajan, K Lalkishore
    International Journal of Computer Science and Network Security 9 (1), 387-394 , 2009
    2009
    Citations: 10
  • An Efficient Discrete Wavelet Transform Architecture with Low Power and Multiplier-Less Structure for Pervasive Biomedical Image Processing Application.
    MA Guptha, SS Rao, R Selvaraj
    EAI Endorsed Transactions on Pervasive Health & Technology 9 (1) , 2023
    2023
    Citations: 6
  • Early detection of dementia disease using data mining techniques
    M Sucharitha, C Chakraborty, S Srinivasa Rao, VSK Reddy
    Internet of Things for Healthcare Technologies, 177-194 , 2020
    2020
    Citations: 6
  • Performance of threshold detection in cognitive radio with improved Otsu’s and recursive one-sided hypothesis testing technique
    P Venkatapathi, H Khan, S SrinivasaRao
    International Journal of Innovative Technology and Exploring Engineering 8 … , 2019
    2019
    Citations: 5
  • ASAF ALOHA protocol for dense RFID systems
    SS Rao, EG Rajan, K Lalkishore
    Wireless Personal Communications 66 (4), 667-681 , 2012
    2012
    Citations: 5
  • RETRACTED ARTICLE: Hybrid Speech Steganography System using SS-RDWT with IPDP-MLE approach
    RC Rao, PVY Jayasree, SS Rao
    Soft Computing 27 (2), 1117-1129 , 2023
    2023
    Citations: 4
  • Spread Spectrum Based Speech Steganography Using RDWT
    RC Rao, PVY Jayasree, SS Rao, PM Kumar
    2021 Second International Conference on Electronics and Sustainable … , 2021
    2021
    Citations: 2
  • An integrated VLSI architecture for forward and backward lifting scheme discrete wavelet transform using FinFET device
    MA Guptha, SS Rao, R Selvaraj
    Soft Computing and Signal Processing: Proceedings of 3rd ICSCSP 2020, Volume … , 2021
    2021
    Citations: 2
  • Ideal frequency rendezvousing for multiuser communication (IFRMC) over cognitive radio network
    C Suneetha, S Srinivasa Rao, KS Ramesh
    International Journal of Speech Technology 23 (3), 537-547 , 2020
    2020
    Citations: 2
  • Multi-stage decimation with hybrid CIC-polyphase filtering for IoT gateway sample rate conversion
    S Pinjerla, SS Rao, PC Reddy
    Scientific Reports , 2025
    2025
    Citations: 1
  • Basic Framework of Different Steganography Techniques for Security Applications
    RC Rao, PVY Jayasree, SS Rao, GS Yeshwanth, KRS Megana, K Shreya, ...
    International Conference on Soft Computing and Signal Processing, 571-583 , 2021
    2021
    Citations: 1
  • Convolution based multilevel DWT architecture using distributed arithmetic and FIR bi-orthogonal filter for two-dimensional data analysis
    MA Guptha, S Srinivasa Rao, R Selvaraj
    Advances in Smart Communication and Imaging Systems: Select Proceedings of … , 2021
    2021
    Citations: 1
  • Adaptive Sampling Rate Converter for Wireless Sensor Networks
    P Swetha, S Srinivasa Rao, P Chandrasekhar Reddy
    Soft Computing and Signal Processing: Proceedings of ICSCSP 2018, Volume 1 … , 2019
    2019
    Citations: 1
  • Retraction Note: Hybrid Speech Steganography System using SS-RDWT with IPDP-MLE approach
    RC Rao, PVY Jayasree, SS Rao
    Soft Computing 28 (Suppl 2), 989-989 , 2024
    2024
  • Clusters-based rendezvousing approach for scheduling the flash crowd transmissions over cognitive radio networks
    C Suneetha, SS Rao, KS Ramesh
    International Journal of Ultra Wideband Communications and Systems 5 (1), 1-11 , 2022
    2022
  • Architecture Using Distributed Arithmetic and FIR Bi-orthogonal Filter for Two-Dimensional Data Analysis
    MA Guptha, SS Rao, R Selvaraj
    Advances in Smart Communication and Imaging Systems: Select Proceedings of … , 2021
    2021