In ZigBee network, the network address assignment scheme is simple, but it restricts the child device number of some parent and the maximum network depth. And the scheme can not ensure all the devices to assign the addresses, even if there are some remaining address spaces. So some devices that are called orphan nodes can not join the network. Based on deeply studying the network formation in ZigBee network, an improved orphan nodes-reduced (IONR) mechanism has been proposed in this paper: using the two reserved bits in beacon payload fully according to the features of ZR and ZED; modifying the connection of joining nodes and potential parents by using the reserved bits and additional commands. The mechanism could reduce the orphan nodes and effectively improve the connectivity of ZigBee network, which avoided additional overhead based on constant length of beacon payload.

In signal processing, a frequently encountered problem is harmonic retrieval in additive colored noise, especially false peaks existence in harmonic signal peaks. The purpose of this paper is to develop an efficient approach to clear the false peaks based on cross-high-order spectral QR decomposition approach. Simulation results indicate that spectral density curve is smooth without false peaks existence. The methods have better in resolving power and performance than previous MUSIC approach. Thus, this approach is ideally suited for harmonic retrieval in additive colored noise and short data conditions, and is also accurate to estimation signal parameter in hybrid colored noises.

On the basis of the present mining algorithm for spatial outliers, this essay brings up a new definition for spatial outliers and a new mining algorithm conforming to the new definition. Also, this essay analyzes the time complexity of such algorithm.

Traditional k-Nearest Neighbor Algorithm (short for KNN) is usually used in the spatial classification; however, the problem of low-speed searching exists in this method. In order to avoid this kind of disadvantage, this paper puts forward a new spatial classification algorithm of K-nearest neighbor based on spatial predicate. This method searches the object set which is similar to the test object in spatial concept and uses spatial predicate to help search the object set, which narrows the searching range and reduces the operating time of KNN algorithm.