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Results are presented that use certain types of restricted recurrent connectivity and anticipation learning with regard to the input, where power law forgetting can indeed be achieved. <\/jats:p>","DOI":"10.1162\/neco_a_00730","type":"journal-article","created":{"date-parts":[[2015,3,16]],"date-time":"2015-03-16T16:23:58Z","timestamp":1426523038000},"page":"1102-1119","source":"Crossref","is-referenced-by-count":8,"title":["Input-Anticipating Critical Reservoirs Show Power Law Forgetting of Unexpected Input Events"],"prefix":"10.1162","volume":"27","author":[{"given":"Norbert Michael","family":"Mayer","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Advanced Institute of Manufacturing with High-tech Innovations, National Chung Cheng University, Min-Hsiung, Chia-Yi, Taiwan"}]}],"member":"281","reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.59.381"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780195395518.001.0001"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.0540-04.2004"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1007\/s12064-011-0146-8"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2006.872357"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2009.01-09-947"},{"key":"B8","first-page":"658","author":"Hajnal M. 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