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Summary: This paper addresses the problem of switching control for systems subject to external disturbances that vary over multiple frequency ranges. Specifically, two different scenarios of disturbance injection are considered; namely, the disturbance may switch between different prescribed frequency ranges, subject to an average dwell time setting, or the disturbance may reside within one of the frequency ranges. To address these scenarios, a disturbance‐triggered control scheme is developed that divides the entire frequency range into low‐, mid‐, and high‐frequency ranges. This scheme ensures closed‐loop stability under average dwell time frequency‐range switching and achieves H∞$$ {H}_{\infty } $$ performance when operated under individual frequency ranges. Synthesis conditions in matrix inequalities are derived to characterize the switching control, and an iterative algorithm is proposed for finding a desired set of controller gains. Finally, two examples are presented to illustrate the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

Summary scATAC-seq is a powerful approach for characterizing cell-type-specific regulatory landscapes. However, it is difficult to benchmark the performance of various scATAC-seq analysis techniques (such as clustering and deconvolution) without having a priori a known set of gold-standard cell types. To simulate scATAC-seq experiments with known cell-type labels, we introduce an efficient and scalable scATAC-seq simulation method (SCAN-ATAC-Sim) that down-samples bulk ATAC-seq data (e.g. from representative cell lines or tissues). Our protocol uses a consistent but tunable signal-to-noise ratio across cell types in a scATAC-seq simulation for integrating bulk experiments with different levels of background noise, and it independently samples twice without replacement to account for the diploid genome. Because it uses an efficient weighted reservoir sampling algorithm and is highly parallelizable with OpenMP, our implementation in C++ allows millions of cells to be simulated in less than an hour on a laptop computer. Availability and implementation SCAN-ATAC-Sim is available at scan-atac-sim.gersteinlab.org. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]