...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Transactions on Information Theory >One-Bit Compressive Sensing With Norm Estimation
【24h】

One-Bit Compressive Sensing With Norm Estimation

机译：范数估计的一比特压缩感知

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Consider the recovery of an unknown signal from quantized linear measurements. In the one-bit compressive sensing setting, one typically assumes that is sparse, and that the measurements are of the form . Since such measurements give no information on the norm of , recovery methods typically assume that . We show that if one allows more generally for quantized affine measurements of the form , and if the vectors are random, an appropriate choice of the affine shifts allows norm recovery to be easily incorporated into existing methods for one-bit compressive sensing. In addition, we show that for arbitrary fixed in the annulus , one may estimate the norm up to additive error from such binary measurements thr- ugh a single evaluation of the inverse Gaussian error function. Finally, all of our recovery guarantees can be made universal over sparse vectors in the sense that with high probability, one set of measurements and thresholds can successfully estimate all sparse vectors in a Euclidean ball of known radius.
机译：考虑从量化的线性测量中恢复未知信号。在一位压缩感测设置中，通常假定它是稀疏的，并且测量形式为。由于这样的测量没有提供有关范数的信息，因此恢复方法通常假定为。我们表明，如果更普遍地允许对形式的量化仿射测量，并且如果向量是随机的，则仿射偏移的适当选择将使范数恢复易于合并到用于一位压缩感测的现有方法中。另外，我们表明，对于环中的任意固定点，可以通过对高斯逆函数的单次求值，从此类二元测量值估计直至加性误差的范数。最终，我们的所有恢复保证都可以在稀疏向量上通用，因为在一定概率下，一组测量值和阈值可以成功估计已知半径的欧几里得球中的所有稀疏向量。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号