物业管理论文可投哪些期刊

Title: Strategic Property Management: How Can Local Authorities Develop a Property Strategy?Author(s):Virginia GibsonJournal:Property ManagementYear:1994 Volume:12 Issue:3 Page:9 - 14DOI: : MCB UP Ltd之类的给你发你邮箱了记得查收哦~~~~~记得加分^_^

1.现代物业2.房地产（物业管理）

我也问过类似的问题，把朋友回答的转发给你吧：《住宅与房地产》杂志物业版，在深圳，里面有一些实际的管理运营思路方面的文章，推荐看看；《物业教育资讯》杂志，在北京，亚太研究院物业管理研究中心办的，比较专业，行业资讯也较全，有许多实际管理方面的案例，很不错。而且价钱了也很便宜，适合企业中高层管理人员参考，能解决实际问题，实操性好，推荐；《新疆房地产杂志》杂志，在新疆，可能地理位置限制，资源有限，地域性比较强。楼主可斟酌选阅。

The necessity for accurate speech recognition systems capableof handling adverse environments with multiple speakershas in recent years fueled speech separation and enhancementresearch [1, 5, 3, 2, 6, 4]. This has resulted in numeroustechniques with varying degrees of success, most ofwhich employ multiple microphones [1, 3, 2, 6, 4]. Beamformingtechniques, for example, utilize knowledge aboutthe direction of the speech source of interest in order to reducenoise from other directions. The resulting SNR gainis significant as long as a large number of microphones areavailable [6, 4]. Independent Component Analysis (ICA),on the other hand, is capable of producing large SNR gainswith few microphones [1, 3]. However, ICA has severallimitations that have hampered its application in real-worldsituations [1, 6].Interestingly, both of these popular techniques (as wellas many other speech separation techniques) are similar inthe sense that they are not specifically designed to functionfor speech signals. Speech has certain characteristics whoseutilization can provide a significant edge in the de-noisingand signal separation tasks [2, 5].In this paper, we extend the phase error filtering techniqueinitially proposed in [2] to include the magnitudesof the two microphones in addition to the phase technique transforms two noisy time-domain signalsrecorded by two microphones into their time-frequency(TF) representations. For each time-frequency componentor block, a phase-error measure is derived from the informationin both microphones. Based on this, the time-frequencyblock for each microphone is scaled by a masking value betweenzero and one. Basically, TF blocks with large phaseerrorsare ‘punished’ by a small mask value (0) and TFblocks with small phase-errors are ‘rewarded’ by a largemask value (1).In the following sections, we formulate four different TFmasks and analyze them theoretically, through SNR-gainsimulations, and digit recognition experiments.