activity
20152021
most citedSampling Requirements for Stable Autoregressive Estimation

14 citations · 26 across the 5 of their papers we have counts for

collaborators

6 papers

eess.SP2021

Feasibility Study on Intra-Grid Location Estimation Using Power ENF Signals

Ravi Garg, Adi Hajj-Ahmad, Min Wu

The Electric Network Frequency (ENF) is a signature of power distribution networks that can be captured by multimedia recordings made in areas where there is electrical activity. T…

cs.CR2018

Tackling Android Stego Apps in the Wild

Wenhao Chen, Li Lin, Min Wu +1

Digital image forensics is a young but maturing field, encompassing key areas such as camera identification, detection of forged images, and steganalysis. However, large gaps exist…

stat.ML2016★ 3 cited

Efficient Estimation of Compressible State-Space Models with Application to Calcium Signal Deconvolution

Abbas Kazemipour, Ji Liu, Patrick Kanold +2

In this paper, we consider linear state-space models with compressible innovations and convergent transition matrices in order to model spatiotemporally sparse transient events. We…

cs.IT2016★ 14 cited

Sampling Requirements for Stable Autoregressive Estimation

Abbas Kazemipour, Sina Miran, Piya Pal +2

We consider the problem of estimating the parameters of a linear univariate autoregressive model with sub-Gaussian innovations from a limited sequence of consecutive observations.…

cs.MM2016★ 9 cited

Impact Analysis of Baseband Quantizer on Coding Efficiency for HDR Video

Chau-Wai Wong, Guan-Ming Su, Min Wu

Digitally acquired high dynamic range (HDR) video baseband signal can take 10 to 12 bits per color channel. It is economically important to be able to reuse the legacy 8 or 10-bit…

cs.NE2015

Robust Estimation of Self-Exciting Generalized Linear Models with Application to Neuronal Modeling

Abbas Kazemipour, Min Wu, Behtash Babadi

We consider the problem of estimating self-exciting generalized linear models from limited binary observations, where the history of the process serves as the covariate. We analyze…