activity
20182024
most citedTheory and investigation of acoustic multiple-input multiple-output systems based on spherical arrays in a room

11 citations · 37 across the 8 of their papers we have counts for

collaborators

8 papers

eess.AS2024★ 11 cited

Theory and investigation of acoustic multiple-input multiple-output systems based on spherical arrays in a room

Hai Morgenstern, Boaz Rafaely, Franz Zotter

Spatial attributes of room acoustics have been widely studied using microphone and loudspeaker arrays. However, systems that combine both arrays, referred to as multiple-input mult…

eess.AS2024★ 4 cited

Modal smoothing for analysis of room reflections measured with spherical microphone and loudspeaker arrays

Hai Morgenstern, Boaz Rafaely

Spatial analysis of room acoustics is an ongoing research topic. Microphone arrays have been employed for spatial analyses with an important objective being the estimation of the d…

eess.AS2024★ 7 cited

Spatial Reverberation and Dereverberation using an Acoustic Multiple-Input Multiple-Output System

Hai Morgenstern, Boaz Rafaely

Methods are proposed for modifying the reverberation characteristics of sound fields in rooms by employing a loudspeaker with adjustable directivity, realized with a compact spheri…

eess.AS2024★ 7 cited

Design framework for spherical microphone and loudspeaker arrays in a multiple-input multiple-output system

Hai Morgenstern, Boaz Rafaely, Markus Noisternig

Spherical microphone arrays (SMAs) and spherical loudspeaker arrays (SLAs) facilitate the study of room acoustics due to the three-dimensional analysis they provide. More recently,…

q-fin.TR2022

Neural Augmented Kalman Filtering with Bollinger Bands for Pairs Trading

Amit Milstein, Haoran Deng, Guy Revach +2

Pairs trading is a family of trading techniques that determine their policies based on monitoring the relationships between pairs of assets. A common pairs trading approach relies…

cs.LG2022★ 6 cited

Decentralized Low-Latency Collaborative Inference via Ensembles on the Edge

May Malka, Erez Farhan, Hai Morgenstern +1

The success of deep neural networks (DNNs) is heavily dependent on computational resources. While DNNs are often employed on cloud servers, there is a growing need to operate DNNs…

cs.CV2020★ 1 cited

Self-Supervised Dynamic Networks for Covariate Shift Robustness

Tomer Cohen, Noy Shulman, Hai Morgenstern +2

As supervised learning still dominates most AI applications, test-time performance is often unexpected. Specifically, a shift of the input covariates, caused by typical nuisances l…

cs.SD2018★ 1 cited

Description of algorithms for Ben-Gurion University Submission to the LOCATA challenge

Lior Madmoni, Hanan Beit-On, Hai Morgenstern +1

This paper summarizes the methods used to localize the sources recorded for the LOCalization And TrAcking (LOCATA) challenge. The tasks of stationary sources and arrays were consid…