Least absolute deviation estimation for general autoregressive moving average time‐series models

We study least absolute deviation (LAD) estimation for general autoregressive moving average time‐series models that may be noncausal, noninvertible or both. For ARMA models with Gaussian noise, causality and invertibility are assumed for the parameterization to be identifiable. The assumptions, however, are not required for models with non‐Gaussian noise, and hence are removed in our study. We derive a functional limit theorem for random processes based on an LAD objective function, and establish the consistency and asymptotic normality of the LAD estimator. The performance of the estimator is evaluated via simulation and compared with the asymptotic theory. Application to real data is also provided.     

一种相移键控数字图像水印算法

根据相移键控原理．提出了一种不可逆DWT域二相相位键控数字图像水印算法．水印信号为二值图像，用不同相位的正弦信号将水印调制后嵌入到数字图像DWT变换系数中；用提取的同频率正弦信号的相位进行水印提取；该方法嵌入的水印具有非常好的安全性，且水印提取不需要原始未加水印的图像．实验结果表明该方法具有很好的不可见性；对JPEG压缩、图像加噪声和图像滤波等常见的图像处理具有极强的鲁棒性．     

Noninvertible fingerprint transforms: Categorization of design mechanisms and discussion of evaluation techniques

ABSTRACT

The explosive growth in fingerprint technologies within the past decade has seen the emergence of a dedicated field of research into securing fingerprint templates during storage in a database. While new fingerprint template protection techniques are often broadly classified as belonging to the well-known salting, noninvertible transforms, key binding, or key generation categories, methods within each category are currently lacking a sense of organization. This article aims to fill this gap by proposing a categorization of noninvertible fingerprint transforms based on their design mechanisms. Our survey of the current literature in this field reveals two prominent types of approaches, so we classify existing noninvertible fingerprint transforms into two main categories: perturbation-based and histogram-based. We also discuss the evaluation techniques used to assess the robustness of noninvertible fingerprint transforms in the literature. These contributions will serve to help researchers find their bearing in the growing fingerprint template protection field, thereby encouraging a deeper understanding of the field and faster progress in the development of more effective fingerprint template protection schemes.