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Satish Mulleti
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2020 – today
- 2024
- [j12]Akankshya Bhatta
, Sibi Raj B. Pillai
, Tummalapalli Venkata Chandrasekhar Sarma
, Satish Mulleti
:
Velocity Profiling of a Distributed Target in Fluctuating SNR Environments. IEEE Trans. Signal Process. 72: 2467-2482 (2024) - [c18]Garweet Sresth, Ajit Rajwade, Satish Mulleti:
Unlabelled Sensing with Priors: Algorithm and Bounds. ICASSP 2024: 9551-9555 - [c17]Kaushani Majumder, Sibi Raj B. Pillai, Yonina C. Eldar, Satish Mulleti:
Adaptive Sensor Selection with Deterministic Priors for DoA Tracking. ICASSP 2024: 9566-9570 - [c16]Anuj Fulari, Satish Mulleti, Ajit Rajwade:
Unsupervised Model-based Learning for Simultaneous Video Deflickering and Deblotching. WACV 2024: 4105-4113 - 2023
- [j11]Satish Mulleti
, Haiyang Zhang
, Yonina C. Eldar
:
Learning to Sample: Data-Driven Sampling and Reconstruction of FRI Signals. IEEE Access 11: 71048-71062 (2023) - [j10]Satish Mulleti
, Eliya Reznitskiy, Shlomi Savariego, Moshe Namer, Nimrod Glazer, Yonina C. Eldar:
A hardware prototype of wideband high-dynamic range analog-to-digital converter. IET Circuits Devices Syst. 17(4): 181-192 (2023) - [j9]Bahareh Tolooshams
, Satish Mulleti
, Demba E. Ba
, Yonina C. Eldar
:
Unrolled Compressed Blind-Deconvolution. IEEE Trans. Signal Process. 71: 2118-2129 (2023) - [c15]Kaushani Majumder
, Sibi Raj B. Pillai, Satish Mulleti:
Clustered Greedy Algorithm For Large-Scale Sensor Selection. ICASSP 2023: 1-5 - [c14]Satish Mulleti, Yonina C. Eldar:
High-Dynamic Range ADC for Finite-Rate-of-Innovation Signals. ICASSP 2023: 1-5 - [c13]Shaik Basheeruddin Shah, Satish Mulleti, Yonina C. Eldar:
Lasso-Based Fast Residual Recovery For Modulo Sampling. ICASSP 2023: 1-5 - [c12]Yuvraj Singh, Jahnvi Singh Rohela, Satish Mulleti:
Sample-Efficient Robust MMV Recovery Algorithm. ICASSP 2023: 1-5 - [c11]Archishman Biswas, A P. Goutham, Saket Pateriya, Divyang Sureshbhai Jadav, Satish Mulleti, Vikram M. Gadre:
A Novel Embedding Architecture and Score Level Fusion Scheme for Occluded Image Acquisition in Ear Biometrics System. NCC 2023: 1-6 - 2022
- [j8]Hila Naaman
, Satish Mulleti
, Yonina C. Eldar
:
FRI-TEM: Time Encoding Sampling of Finite-Rate-of-Innovation Signals. IEEE Trans. Signal Process. 70: 2267-2279 (2022) - [c10]Satish Mulleti, Haiyang Zhang, Yonina C. Eldar:
Learning to Sample for Sparse Signals. ICASSP 2022: 3363-3367 - [c9]Eyar Azar, Satish Mulleti, Yonina C. Eldar:
Residual Recovery Algorithm for Modulo Sampling. ICASSP 2022: 5722-5726 - [c8]Hila Naaman, Satish Mulleti, Yonina C. Eldar:
Uniqueness and Robustness of Tem-Based FRI Sampling. ISIT 2022: 2631-2636 - [i6]Bahareh Tolooshams, Satish Mulleti, Demba E. Ba, Yonina C. Eldar:
Learning Filter-Based Compressed Blind-Deconvolution. CoRR abs/2209.14165 (2022) - 2021
- [c7]Bahareh Tolooshams, Satish Mulleti, Demba E. Ba, Yonina C. Eldar:
Unfolding Neural Networks for Compressive Multichannel Blind Deconvolution. ICASSP 2021: 2890-2894 - [c6]Pranav Goyal, Satish Mulleti, Anubha Gupta
, Yonina C. Eldar:
DURAS: Deep Unfolded Radar Sensing Using Doppler Focusing. ICASSP 2021: 4070-4074 - [c5]Satish Mulleti, Kiryung Lee, Yonina C. Eldar:
Sub-NYQUIST Multichannel Blind Deconvolution. ICASSP 2021: 5454-5458 - [i5]Hila Naaman, Satish Mulleti, Yonina C. Eldar:
FRI-TEM: Time Encoding Sampling of Finite-Rate-of-Innovation Signals. CoRR abs/2106.05564 (2021) - [i4]Hila Naaman, Satish Mulleti, Yonina C. Eldar, Alejandro Cohen:
Time-Based Quantization for FRI and Bandlimited signals. CoRR abs/2110.01928 (2021) - 2020
- [j7]Satish Mulleti
, Kiryung Lee
, Yonina C. Eldar
:
Identifiability Conditions for Compressive Multichannel Blind Deconvolution. IEEE Trans. Signal Process. 68: 4627-4642 (2020) - [i3]Satish Mulleti, Kiryung Lee, Yonina C. Eldar:
Identifiability Conditions for Compressive Multichannel Blind Deconvolution. CoRR abs/2001.00613 (2020) - [i2]Kumar Vijay Mishra, Satish Mulleti, Yonina C. Eldar:
RaSSteR: Random Sparse Step-Frequency Radar. CoRR abs/2004.05720 (2020) - [i1]Bahareh Tolooshams, Satish Mulleti, Demba E. Ba, Yonina C. Eldar:
Unfolding Neural Networks for Compressive Multichannel Blind Deconvolution. CoRR abs/2010.11391 (2020)
2010 – 2019
- 2018
- [j6]Basty Ajay Shenoy, Satish Mulleti
, Chandra Sekhar Seelamantula
:
On Two-Dimensional Hilbert Integral Equations, Generalized Minimum-Phase Signals, and Phase Retrieval. IEEE Trans. Signal Process. 66(14): 3906-3917 (2018) - 2017
- [j5]Satish Mulleti, Chandra Sekhar Seelamantula:
Paley-Wiener Characterization of Kernels for Finite-Rate-of-Innovation Sampling. IEEE Trans. Signal Process. 65(22): 5860-5872 (2017) - 2016
- [j4]Satish Mulleti, Chandra Sekhar Seelamantula:
Ellipse Fitting Using the Finite Rate of Innovation Sampling Principle. IEEE Trans. Image Process. 25(3): 1451-1464 (2016) - [j3]Basty Ajay Shenoy, Satish Mulleti, Chandra Sekhar Seelamantula:
Exact Phase Retrieval in Principal Shift-Invariant Spaces. IEEE Trans. Signal Process. 64(2): 406-416 (2016) - [j2]Satish Mulleti, Basty Ajay Shenoy, Chandra Sekhar Seelamantula:
FRI Sampling on Structured Nonuniform Grids - Application to Super-Resolved Optical Imaging. IEEE Trans. Signal Process. 64(15): 3841-3853 (2016) - 2015
- [c4]Satish Mulleti, Chandra Sekhar Seelamantula:
Periodic non-uniform sampling for FRI signals. ICASSP 2015: 5942-5946 - 2014
- [j1]Chandra Sekhar Seelamantula, Satish Mulleti:
Super-Resolution Reconstruction in Frequency-Domain Optical-Coherence Tomography Using the Finite-Rate-of-Innovation Principle. IEEE Trans. Signal Process. 62(19): 5020-5029 (2014) - [c3]Sudarshan Nagesh, Satish Mulleti, Chandra Sekhar Seelamantula:
On the role of the Hilbert transform in boosting the performance of the annihilating filter. ICASSP 2014: 1836-1840 - [c2]Satish Mulleti, Chandra Sekhar Seelamantula:
Ellipse fitting using finite rate of innovation principles. ICASSP 2014: 5824-5828 - [c1]Satish Mulleti, Sudarshan Nagesh, Rajesh Langoju, Abhijit Patil, Chandra Sekhar Seelamantula:
Ultrasound image reconstruction using the finite-rate-of-innovation principle. ICIP 2014: 1728-1732
Coauthor Index
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last updated on 2024-08-07 22:30 CEST by the dblp team
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