{"id":"https://openalex.org/W7133296810","doi":"https://doi.org/10.48550/arxiv.2603.00153","title":"Pulse-Driven Neural Architecture: Learnable Oscillatory Dynamics for Robust Continuous-Time Sequence Processing","display_name":"Pulse-Driven Neural Architecture: Learnable Oscillatory Dynamics for Robust Continuous-Time Sequence Processing","publication_year":2026,"publication_date":"2026-02-25","ids":{"openalex":"https://openalex.org/W7133296810","doi":"https://doi.org/10.48550/arxiv.2603.00153"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.00153","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00153","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.00153","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102568122","display_name":"Paras Sharma","orcid":"https://orcid.org/0000-0002-6909-205X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sharma, Paras","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5102568122"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.8159000277519226,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.8159000277519226,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.05260000005364418,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.03150000050663948,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7368999719619751},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.5911999940872192},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5164999961853027},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4814999997615814},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.4481000006198883},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.39010000228881836},{"id":"https://openalex.org/keywords/oscillation","display_name":"Oscillation (cell signaling)","score":0.37459999322891235},{"id":"https://openalex.org/keywords/dynamics","display_name":"Dynamics (music)","score":0.3596000075340271}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7368999719619751},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.5911999940872192},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5164999961853027},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4814999997615814},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4618000090122223},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.4481000006198883},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4404999911785126},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39640000462532043},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.39010000228881836},{"id":"https://openalex.org/C2778439541","wikidata":"https://www.wikidata.org/wiki/Q7106412","display_name":"Oscillation (cell signaling)","level":2,"score":0.37459999322891235},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.3596000075340271},{"id":"https://openalex.org/C28427503","wikidata":"https://www.wikidata.org/wiki/Q13580300","display_name":"Internal model","level":3,"score":0.3578999936580658},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.35440000891685486},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3084999918937683},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2978000044822693},{"id":"https://openalex.org/C2986577269","wikidata":"https://www.wikidata.org/wiki/Q11306265","display_name":"Random noise","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2702000141143799},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.2524999976158142},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.00153","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00153","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.00153","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00153","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"introduce":[1],"PDNA":[2,32],"(Pulse-Driven":[3],"Neural":[4],"Architecture),":[5],"a":[6,37,57,69,120,138],"method":[7],"for":[8,185],"augmenting":[9],"continuous-time":[10,176],"recurrent":[11,62],"networks":[12],"with":[13,49,77,142],"learnable":[14,50],"oscillatory":[15,108,183],"dynamics":[16,109],"that":[17,40,60,106,162,175],"maintain":[18,89],"internal":[19,182],"state":[20],"evolution":[21],"independently":[22],"of":[23,93,155],"external":[24],"input.":[25],"Built":[26],"on":[27,73],"Closed-form":[28],"Continuous-time":[29],"(CfC)":[30],"networks,":[31],"adds":[33],"two":[34],"components:":[35],"(1)":[36],"pulse":[38,135],"module":[39,59],"generates":[41],"structured":[42,107],"oscillations":[43],"$A":[44],"\\cdot":[45],"\\sin(\u03c9t":[46],"+":[47],"\u03c6(h))$":[48],"frequencies":[51],"and":[52,55],"state-dependent":[53],"phase,":[54],"(2)":[56],"self-attend":[58,117],"applies":[61],"self-attention":[63],"to":[64,88,113],"the":[65,86,94,116,134,163],"hidden":[66],"state.":[67],"Through":[68],"controlled":[70],"ablation":[71],"study":[72],"sequential":[74],"MNIST":[75],"(sMNIST)":[76],"five":[78],"random":[79],"seeds,":[80],"we":[81],"evaluate":[82],"gap":[83],"robustness":[84,112],"--":[85],"ability":[87],"performance":[90],"when":[91],"portions":[92],"input":[95,114],"sequence":[96],"are":[97],"removed":[98],"at":[99],"test":[100],"time.":[101],"Our":[102],"key":[103],"finding":[104],"is":[105,165],"significantly":[110],"improve":[111],"interruptions:":[115],"variant":[118,136],"achieves":[119],"statistically":[121],"significant":[122],"2.78":[123],"percentage":[124],"point":[125],"multi-gap":[126],"advantage":[127,141,164],"over":[128],"baseline":[129],"($p":[130],"=":[131,148],"0.041$),":[132],"while":[133],"shows":[137],"4.62":[139],"pp":[140],"large":[143],"effect":[144],"size":[145],"(Cohen's":[146],"$d":[147],"0.87$).":[149],"A":[150],"noise":[151],"control":[152],"(random":[153],"perturbation":[154],"equal":[156],"magnitude)":[157],"provides":[158],"no":[159],"benefit,":[160],"confirming":[161],"structural":[166],"rather":[167],"than":[168],"merely":[169],"dynamic.":[170],"These":[171],"results":[172],"provide":[173],"evidence":[174],"models":[177],"can":[178],"benefit":[179],"from":[180],"biologically-inspired":[181],"mechanisms":[184],"temporal":[186],"robustness.":[187]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-04T00:00:00"}
