9 papers · 1 filter
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…
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…
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…