Publication Information

{'id': 'https://openalex.org/W2042241484', 'doi': 'https://doi.org/10.1109/chicc.2014.6896218', 'title': 'Variable step-size compressed sensing-based sparsity adaptive matching pursuit algorithm for speech reconstruction', 'display_name': 'Variable step-size compressed sensing-based sparsity adaptive matching pursuit algorithm for speech reconstruction', 'publication_year': 2014, 'publication_date': '2014-07-01', 'ids': {'openalex': 'https://openalex.org/W2042241484', 'doi': 'https://doi.org/10.1109/chicc.2014.6896218', 'mag': '2042241484'}, 'language': 'en', 'primary_location': {'is_oa': False, 'landing_page_url': 'https://doi.org/10.1109/chicc.2014.6896218', 'pdf_url': None, 'source': None, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, 'type': 'article', 'type_crossref': 'proceedings-article', 'indexed_in': ['crossref'], 'open_access': {'is_oa': False, 'oa_status': 'closed', 'oa_url': None, 'any_repository_has_fulltext': False}, 'authorships': [{'author_position': 'first', 'author': {'id': 'https://openalex.org/A5100701158', 'display_name': 'Zhiwen Yu', 'orcid': 'https://orcid.org/0000-0002-0935-5890'}, 'institutions': [{'id': 'https://openalex.org/I41198531', 'display_name': 'Nanjing University of Posts and Telecommunications', 'ror': 'https://ror.org/043bpky34', 'country_code': 'CN', 'type': 'education', 'lineage': ['https://openalex.org/I41198531']}], 'countries': ['CN'], 'is_corresponding': True, 'raw_author_name': 'Zhiwen Yu', 'raw_affiliation_strings': ['College of Telecommunication & Information Engineering, Nanjing Univ. of Posts and Telecommunications, 210003, China'], 'affiliations': [{'raw_affiliation_string': 'College of Telecommunication & Information Engineering, Nanjing Univ. of Posts and Telecommunications, 210003, China', 'institution_ids': ['https://openalex.org/I41198531']}]}], 'institution_assertions': [], 'countries_distinct_count': 1, 'institutions_distinct_count': 1, 'corresponding_author_ids': ['https://openalex.org/A5100701158'], 'corresponding_institution_ids': ['https://openalex.org/I41198531'], 'apc_list': None, 'apc_paid': None, 'fwci': 0.331, 'has_fulltext': True, 'fulltext_origin': 'ngrams', 'cited_by_count': 10, 'citation_normalized_percentile': {'value': 0.883976, 'is_in_top_1_percent': False, 'is_in_top_10_percent': False}, 'cited_by_percentile_year': {'min': 86, 'max': 87}, 'biblio': {'volume': None, 'issue': None, 'first_page': '7344', 'last_page': '7349'}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T10500', 'display_name': 'Sparse and Compressive Sensing Techniques', 'score': 1.0, 'subfield': {'id': 'https://openalex.org/subfields/2206', 'display_name': 'Computational Mechanics'}, 'field': {'id': 'https://openalex.org/fields/22', 'display_name': 'Engineering'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, 'topics': [{'id': 'https://openalex.org/T10500', 'display_name': 'Sparse and Compressive Sensing Techniques', 'score': 1.0, 'subfield': {'id': 'https://openalex.org/subfields/2206', 'display_name': 'Computational Mechanics'}, '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/T11447', 'display_name': 'Blind Source Separation Techniques', 'score': 0.9992, 'subfield': {'id': 'https://openalex.org/subfields/1711', 'display_name': 'Signal Processing'}, '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/T11739', 'display_name': 'Microwave Imaging and Scattering Analysis', 'score': 0.9983, 'subfield': {'id': 'https://openalex.org/subfields/2204', 'display_name': 'Biomedical Engineering'}, 'field': {'id': 'https://openalex.org/fields/22', 'display_name': 'Engineering'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}], 'keywords': [{'id': 'https://openalex.org/keywords/pruning', 'display_name': 'Pruning', 'score': 0.6815591}, {'id': 'https://openalex.org/keywords/reconstruction-algorithm', 'display_name': 'Reconstruction algorithm', 'score': 0.4421733}, {'id': 'https://openalex.org/keywords/signal-reconstruction', 'display_name': 'Signal reconstruction', 'score': 0.43648577}], 'concepts': [{'id': 'https://openalex.org/C156872377', 'wikidata': 'https://www.wikidata.org/wiki/Q6786281', 'display_name': 'Matching pursuit', 'level': 3, 'score': 0.76574135}, {'id': 'https://openalex.org/C11413529', 'wikidata': 'https://www.wikidata.org/wiki/Q8366', 'display_name': 'Algorithm', 'level': 1, 'score': 0.75610316}, {'id': 'https://openalex.org/C108010975', 'wikidata': 'https://www.wikidata.org/wiki/Q500094', 'display_name': 'Pruning', 'level': 2, 'score': 0.6815591}, {'id': 'https://openalex.org/C124851039', 'wikidata': 'https://www.wikidata.org/wiki/Q2665459', 'display_name': 'Compressed sensing', 'level': 2, 'score': 0.6610627}, {'id': 'https://openalex.org/C41008148', 'wikidata': 'https://www.wikidata.org/wiki/Q21198', 'display_name': 'Computer science', 'level': 0, 'score': 0.6240944}, {'id': 'https://openalex.org/C51823790', 'wikidata': 'https://www.wikidata.org/wiki/Q504353', 'display_name': 'Greedy algorithm', 'level': 2, 'score': 0.5631166}, {'id': 'https://openalex.org/C177264268', 'wikidata': 'https://www.wikidata.org/wiki/Q1514741', 'display_name': 'Set (abstract data type)', 'level': 2, 'score': 0.50177026}, {'id': 'https://openalex.org/C165064840', 'wikidata': 'https://www.wikidata.org/wiki/Q1321061', 'display_name': 'Matching (statistics)', 'level': 2, 'score': 0.4914359}, {'id': 'https://openalex.org/C2779898584', 'wikidata': 'https://www.wikidata.org/wiki/Q7820109', 'display_name': 'Reconstruction algorithm', 'level': 3, 'score': 0.4421733}, {'id': 'https://openalex.org/C70958404', 'wikidata': 'https://www.wikidata.org/wiki/Q7512728', 'display_name': 'Signal reconstruction', 'level': 4, 'score': 0.43648577}, {'id': 'https://openalex.org/C182365436', 'wikidata': 'https://www.wikidata.org/wiki/Q50701', 'display_name': 'Variable (mathematics)', 'level': 2, 'score': 0.43023407}, {'id': 'https://openalex.org/C153180895', 'wikidata': 'https://www.wikidata.org/wiki/Q7148389', 'display_name': 'Pattern recognition (psychology)', 'level': 2, 'score': 0.33627677}, {'id': 'https://openalex.org/C141379421', 'wikidata': 'https://www.wikidata.org/wiki/Q6094427', 'display_name': 'Iterative reconstruction', 'level': 2, 'score': 0.31133464}, {'id': 'https://openalex.org/C33923547', 'wikidata': 'https://www.wikidata.org/wiki/Q395', 'display_name': 'Mathematics', 'level': 0, 'score': 0.27954262}, {'id': 'https://openalex.org/C154945302', 'wikidata': 'https://www.wikidata.org/wiki/Q11660', 'display_name': 'Artificial intelligence', 'level': 1, 'score': 0.2732317}, {'id': 'https://openalex.org/C104267543', 'wikidata': 'https://www.wikidata.org/wiki/Q208163', 'display_name': 'Signal processing', 'level': 3, 'score': 0.2184993}, {'id': 'https://openalex.org/C134306372', 'wikidata': 'https://www.wikidata.org/wiki/Q7754', 'display_name': 'Mathematical analysis', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C105795698', 'wikidata': 'https://www.wikidata.org/wiki/Q12483', 'display_name': 'Statistics', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C76155785', 'wikidata': 'https://www.wikidata.org/wiki/Q418', 'display_name': 'Telecommunications', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C554190296', 'wikidata': 'https://www.wikidata.org/wiki/Q47528', 'display_name': 'Radar', 'level': 2, 'score': 0.0}, {'id': 'https://openalex.org/C6557445', 'wikidata': 'https://www.wikidata.org/wiki/Q173113', 'display_name': 'Agronomy', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C86803240', 'wikidata': 'https://www.wikidata.org/wiki/Q420', 'display_name': 'Biology', 'level': 0, 'score': 0.0}, {'id': 'https://openalex.org/C199360897', 'wikidata': 'https://www.wikidata.org/wiki/Q9143', 'display_name': 'Programming language', 'level': 1, 'score': 0.0}], 'mesh': [], 'locations_count': 1, 'locations': [{'is_oa': False, 'landing_page_url': 'https://doi.org/10.1109/chicc.2014.6896218', 'pdf_url': None, 'source': None, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}], 'best_oa_location': None, 'sustainable_development_goals': [{'score': 0.5, 'display_name': 'Industry, innovation and infrastructure', 'id': 'https://metadata.un.org/sdg/9'}], 'grants': [], 'datasets': [], 'versions': [], 'referenced_works_count': 13, 'referenced_works': ['https://openalex.org/W1977252496', 'https://openalex.org/W2046658845', 'https://openalex.org/W2050834445', 'https://openalex.org/W2099100030', 'https://openalex.org/W2100037283', 'https://openalex.org/W2104424128', 'https://openalex.org/W2127271355', 'https://openalex.org/W2129131372', 'https://openalex.org/W2145096794', 'https://openalex.org/W2151693816', 'https://openalex.org/W2160979406', 'https://openalex.org/W2289917018', 'https://openalex.org/W4250955649'], 'related_works': ['https://openalex.org/W3083878955', 'https://openalex.org/W2907652444', 'https://openalex.org/W2587863204', 'https://openalex.org/W2551136801', 'https://openalex.org/W2545991987', 'https://openalex.org/W2381127329', 'https://openalex.org/W2322507706', 'https://openalex.org/W2262109992', 'https://openalex.org/W2039122851', 'https://openalex.org/W1964291319'], 'abstract_inverted_index': {'This': [0, 56, 142], 'paper': [1], 'presents': [2], 'a': [3, 65, 84, 120], 'novel': [4, 118], 'greedy': [5, 37], 'reconstruction': [6, 61, 140, 153, 158], 'algorithm': [7, 19, 29, 38, 46, 174, 178], 'for': [8, 21, 108], 'speech': [9, 185], 'signal,': [10], 'named': [11], 'the': [12, 24, 35, 48, 60, 70, 92, 110, 114, 117, 128, 139, 145, 152, 172, 176], 'variable': [13], 'step-size': [14], 'sparsity': [15, 39, 94, 111, 130, 149], 'adaptive': [16, 40], 'matching': [17, 41], 'pursuit': [18, 42], '(short': [20], 'VSSAMP).': [22], 'As': [23], 'name': [25], 'implies,': [26], 'this': [27, 104, 165], 'modified': [28, 173], 'achieves': [30], 'an': [31], 'improvement': [32], 'compared': [33], 'with': [34], 'state-of-the-art': [36], '(SAMP).': [43], 'The': [44, 78, 155, 167], 'new': [45], 'varies': [47], 'step': [49, 79, 97, 122, 143], 'size,': [50], 'which': [51, 125], 'is': [52, 81, 99, 106, 123], 'fixed': [53], 'in': [54, 164], 'SAMP.': [55], 'innovation': [57], 'can': [58, 126], 'accelerate': [59], 'speed': [62, 161], 'and': [63, 103, 150, 160, 184], 'demonstrate': [64], 'better': [66], 'performance': [67, 159], 'on': [68, 137], 'estimating': [69, 109], 'true': [71], "signal's": [72], 'support': [73], 'set': [74, 82], 'to': [75, 83, 90], 'some': [76], 'extent.': [77], 'size': [80, 98], 'large': [85], 'value': [86], 'initially': [87], 'so': [88], 'as': [89], 'approach': [91], 'real': [93], 'quickly.': [95], 'Afterwards,': [96], 'cut': [100], 'down': [101], 'gradually': [102], 'mechanism': [105], 'benefit': [107], 'accurately.': [112], 'At': [113], 'end': [115], 'of': [116, 147, 157], 'method,': [119], 'pruning': [121], 'utilized': [124], 'decrease': [127], 'estimated': [129, 148], 'one': [131, 134], 'atom': [132], 'by': [133], 'atom,': [135], 'based': [136], 'reducing': [138], 'error.': [141], 'increases': [144], 'accuracy': [146], 'enhances': [151], 'performance.': [154], 'comparisions': [156], 'are': [162], 'exhibited': [163], 'paper.': [166], 'simulation': [168], 'results': [169], 'show': [170], 'that': [171], 'outperforms': [175], 'SAMP': [177], 'when': [179], 'reconstructing': [180], 'absolutely': [181], 'sparse': [182], 'signals': [183], 'signals.': [186]}, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W2042241484', 'counts_by_year': [{'year': 2024, 'cited_by_count': 2}, {'year': 2023, 'cited_by_count': 2}, {'year': 2021, 'cited_by_count': 1}, {'year': 2020, 'cited_by_count': 2}, {'year': 2019, 'cited_by_count': 1}, {'year': 2018, 'cited_by_count': 1}, {'year': 2017, 'cited_by_count': 1}], 'updated_date': '2025-01-08T05:05:31.706390', 'created_date': '2016-06-24'}