Novel Z-Domain precoding method for blind separation of spatially correlated signals

In this paper, we address the problem of blind separation of spatially correlated signals, which is encountered in some emerging applications, e.g., distributed wireless sensor networks and wireless surveillance systems. We preprocess the source signals in transmitters prior to transmission. Specifically, the source signals are first filtered by a set of properly designed precoders and then the coded signals are transmitted. On the receiving side, the Z-domain features of the precoders are exploited to separate the coded signals, from which the source signals are recovered. Based on the proposed precoders, a closed-form algorithm is derived to estimate the coded signals and the source signals. Unlike traditional blind source separation approaches, the proposed method does not require the source signals to be uncorrelated, sparse, or nonnegative. Compared with the existing precoder-based approach, the new method uses precoders with much lower order, which reduces the delay in data transmission and is easier to implement in practice.

Image encryption based on compressed sensing and blind source separation

A novel image encryption scheme based on compressed sensing and blind source separation is proposed in this work, where there is no statistical requirement to plaintexts. In the proposed method, for encryption, the plaintexts and keys are mixed with each other using a underdetermined matrix first, and then compressed under a project matrix. As a result, it forms a difficult underdetermined blind source separation (UBSS) problem without statistical features of sources. Regarding the decryption, given the keys, a new model will be constructed, which is solvable under compressed sensing (CS) frame. Due to the usage of CS technology, the plaintexts are compressed into the data with smaller size when they are encrypted. Meanwhile, they can be decrypted from parts of the received data packets and thus allows to lose some packets. This is beneficial for the proposed encryption method to suit practical communication systems. Simulations are given to illustrate the availability and the superiority of our method.

Radio frequency energy harvesting from a feeding source in a passive deep brain stimulation device for murine preclinical research

This paper presents the development of an energy harvesting circuit for use with a head-mountable deep brain stimulation (DBS) device. It consists of a circular planar inverted-F antenna (PIFA) and a Schottky diode-based Cockcroft-Walton 4-voltage rectifier. The PIFA has the volume of π × 10(2) × 1.5 mm(3), resonance frequency of 915 MHz, and bandwidth of 16 MHz (909-925 MHz) at a return loss of -10 dB. The rectifier offers maximum efficiency of 78% for the input power of -5 dBm at a 5 kΩ load resistance. The developed rectenna operates efficiently at 915 MHz for the input power within -15 dBm to +5 dBm. For operating a DBS device, the DC voltage of 2 V is recorded from the rectenna terminal at a distance of 55 cm away from a 26.77 dBm transmitter in free space. An in-vitro test of the DBS device is presented.