15 citations · 29 across the 24 of their papers we have counts for
27 papers
Identifiability and Joint Recovery of a Structured Signal Ensemble From Sub-Nyquist Samples
Kumari Priyanka, Satish Mulleti
Efficient acquisition of correlated continuous-time signals is critical in applications such as distributed sensor networks and array processing. However, existing correlation mode…
Fold First, Detect Directly: Communication Symbol Detection Without Unfolding for Low-Bitrate Modulo-ADCs
Krunal Vaghela, Kumar Appaiah, Satish Mulleti
Modulo-folding analog-to-digital converters (MF-ADCs) enable low-dynamic-range quantizers to sample high-amplitude signals without clipping. However, downstream processing traditio…
Tunable Domain Adaptation Using Unfolding
Snehaa Reddy, Jayaprakash Katual, Satish Mulleti
Machine learning models often struggle to generalize across domains with varying data distributions, such as differing noise levels, leading to degraded performance. Traditional st…
Adaptive Non-Uniform Sampling of Bandlimited Signals via Algorithm-Encoder Co-Design
Kaluguri Yashaswini, Anshu Arora, Satish Mulleti
We propose an adaptive non-uniform sampling framework for bandlimited signals based on an algorithm-encoder co-design perspective. By revisiting the convergence analysis of iterati…
Two-Dimensional Tomographic Reconstruction From Projections With Unknown Angles and Unknown Spatial Shifts
Shreyas Jayant Grampurohit, Satish Mulleti, Ajit Rajwade
In parallel beam computed tomography (CT), an object is reconstructed from a series of projections taken at different angles. However, in some industrial and biomedical imaging app…
A Non-Uniform Quantization Framework for Time-Encoding Machines
Kaluguri Yashaswini, Anshu Arora, Satish Mulleti
Time encoding machines (TEMs) provide an event-driven alternative to classical uniform sampling, enabling power-efficient representations without a global clock. While prior work a…
Verifiable Deep Quantitative Group Testing
Shreyas Jayant Grampurohit, Satish Mulleti, Ajit Rajwade
We present a neural network-based framework for solving the quantitative group testing (QGT) problem that achieves both high decoding accuracy and structural verifiability. In QGT,…
Linear-Bias Time Encoding for Low-Rate Quantized Representation of Bandlimited Signals
Anshu Arora, Kaluguri Yashaswini, Satish Mulleti
Integrate-and-fire time encoding machines (IF-TEMs) provide an efficient framework for asynchronous sampling of bandlimited signals through discrete firing times. However, conventi…
Dictionary-Based Deblurring for Unpaired Data
Alok Panigrahi, Jayaprakash Katual, Satish Mulleti
Effective image deblurring typically relies on large and fully paired datasets of blurred and corresponding sharp images. However, obtaining such accurately aligned data in the rea…
Self-Calibrating Integrate-and-Fire Time Encoding Machine
Maya Mekel, Vered Karp, Satish Mulleti +1
In this paper, we introduce a novel self-calibrating integrate-and-fire time encoding machine (S-IF-TEM) that enables simultaneous parameter estimation and signal reconstruction du…
Compressed Sensing Based Residual Recovery Algorithms and Hardware for Modulo Sampling
Shaik Basheeruddin Shah, Satish Mulleti, Yonina C. Eldar
Analog-to-Digital Converters (ADCs) are essential components in modern data acquisition systems. A key design challenge is accommodating high dynamic range (DR) input signals witho…
Subsampling of Correlated Graph Signals
Rishabh Ravi, Kaushani Majumder, Kalp Vyas +1
Graph signals are functions of the underlying graph. When the edge-weight between a pair of nodes is high, the corresponding signals generally have a higher correlation. As a resul…
Blind-Adaptive Quantizers
Aman Rishal Chemmala, Satish Mulleti
Sampling and quantization are crucial in digital signal processing, but quantization introduces errors, particularly due to distribution mismatch between input signals and quantize…
Power-Efficient Sampling
Satish Mulleti, Timur Zirtiloglu, Arman Tan +2
Analog-to-digital converters (ADCs) facilitate the conversion of analog signals into a digital format. While the specific designs and settings of ADCs can vary depending on their a…
Modulation For Modulo: A Sampling-Efficient High-Dynamic Range ADC
Satish Mulleti, Resham Yashwanth Kumar, Laxmeesha Somappa
In high-dynamic range (HDR) analog-to-digital converters (ADCs), having many quantization bits minimizes quantization errors but results in high bit rates, limiting their applicati…
Unlabelled Sensing with Priors: Algorithm and Bounds
Garweet Sresth, Ajit Rajwade, Satish Mulleti
In this study, we consider a variant of unlabelled sensing where the measurements are sparsely permuted, and additionally, a few correspondences are known. We present an estimator…
Greedy Selection for Heterogeneous Sensors
Kaushani Majumder, SibiRaj B. Pillai, Satish Mulleti
Simultaneous operation of all sensors in a large-scale sensor network is power-consuming and computationally expensive. Hence, it is desirable to select fewer sensors. A greedy alg…
A Hardware Prototype of Wideband High-Dynamic Range ADC
Satish Mulleti, Eliya Reznitskiy, Shlomi Savariego +3
Key parameters of analog-to-digital converters (ADCs) are their sampling rate and dynamic range. Power consumption and cost of an ADC are directly proportional to the sampling rate…
Unrolled Compressed Blind-Deconvolution
Bahareh Tolooshams, Satish Mulleti, Demba Ba +1
The problem of sparse multichannel blind deconvolution (S-MBD) arises frequently in many engineering applications such as radar/sonar/ultrasound imaging. To reduce its computationa…
Modulo Sampling of FRI Signals
Satish Mulleti, Yonina C. Eldar
The dynamic range of an analog-to-digital converter (ADC) is critical during sampling of analog signals. A modulo operation prior to sampling can be used to enhance the effective d…
Robust Unlimited Sampling Beyond Modulo
Eyar Azar, Satish Mulleti, Yonina C. Eldar
Analog to digital converters (ADCs) act as a bridge between the analog and digital domains. Two important attributes of any ADC are sampling rate and its dynamic range. For bandlim…
Residual Recovery Algorithm For Modulo Sampling
Eyar Azar, Satish Mulleti, Yonina C. Eldar
Two important attributes of analog to digital converters (ADCs) are its sampling rate and dynamic range. The sampling rate should be greater than or equal to the Nyquist rate for b…
Learning to Sample: Data-Driven Sampling and Reconstruction of FRI Signals
Satish Mulleti, Haiyang Zhang, Yonina C. Eldar
Finite-rate-of-innovation (FRI) signals are ubiquitous in applications such as radar, ultrasound, and time of flight imaging. Due to their finite degrees of freedom, FRI signals ca…
FRI-TEM: Time Encoding Sampling of Finite-Rate-of-Innovation Signals
Hila Naaman, Satish Mulleti, Yonina C. Eldar
Classical sampling is based on acquiring signal amplitudes at specific points in time, with the minimal sampling rate dictated by the degrees of freedom in the signal. The samplers…