Ship interior NOISE produced by engine room disturbs the crews and the workers. Also, it causes lots of complications for the crews and the passengers in the ship. ACTIVE NOISE CANCELLATION (ANC) is based on the destructive interference between the primary NOISE and generated NOISE from the secondary source. In this research, performance of the static and dynamic neural networks is evaluated in ACTIVE CANCELLATION of sound NOISE. For this reason, MLP and RBF are designed and trained as static neural networks. After training, performance of static and dynamic networks in NOISE attenuation are compared. In order to compare the networks appropriately, training and test samples are similar. Moreover, equal number of layers and neurons are considered for the networks. NOISE signals from a SPIB database are used in simulation procedures. The simulation results show that designed neural networks present proper performance in ANC because of using training and validation samples in training process. As it is seen, the trained dynamic network and RBF neural network show better performance in NOISE attenuation than MLP network and achieve 1 dB NOISE attenuation more than MLP network.

In this paper, a novel LNA design based on improved NOISE CANCELLATION technique in the frequency range of 27 to 31 GHz.is presented The proposed LNA is suitable for millimeter wave 5G wireless communication. The first stage of this two-stage LNA is designed with NOISE cancelation approach to decrease the NOISE figure of the system. In order to improve the design method, we utilizes a negative feedback by implementing a couple inductor with a transformer connection. The negative feedback provides an acceptable input matching and control the gain to increase the band width. The cascode structure is used in the second stage for its higher gain and stability and better reverse isolation at millimeter wave frequency. Furthermore, an inductor is utilized to boost the gain with neutralizing the capacitance of node between two transistors in a cascode structure. The CMOS silicon on insulator (SOI) is utilized to provide a high level of integration and low power consumption with the minimum cost. The proposed LNA is designed with 130 nm CMOS technology and has 22.14 dB gain with 1.86 dB NOISE figure at 29 GHz. The 3-dB bandwidth of the designed LNA is 4 GHz (14%) and its DC power consumption is 33.4 mW. The IIP3 is -16dBm and input reflection coefficient is better than -10dBm in the frequency range of interest. The proposed LNA is simulated by ADS software.

Reaction wheels (RWs) used for attitude control of space vehicle systems usually encounter with undesired wide band NOISEs. These NOISEs which significantly affect the performance of regulator controller must tune the review or review rate of RWs. According to wide frequency band of NOISEs in RWs the common approaches of NOISE CANCELLATION cannot conveniently reduce the effects of the NOISE. Therefore, the advanced analyzer of frequency domain signal processing such as wavelets must be used to realize the NOISE CANCELLATION. In this regards, only the online application of wavelets can be practical. In this paper, an online ACTIVE NOISE canceller based on online wavelet theory is employed to omit the effects of undesired NOISE. In this way, dynamic identification of a RW as well as wavelet delay compensation are used simultaneously to design an ACTIVE NOISE CANCELLATION system. Numerical and experimental investigations of KNTU test setup as a hard ware in the loop system show the preferences of the proposed method of online NOISE CANCELLATION.

The least mean square (LMS) adaptive algorithm is widely used in acoustic NOISE CANCELLATION (ANC) scenario. In this scenario, speech signals usually have high amplitude and sudden variations that are modeled by impulsive disturbances and it is well known that the acoustic channels usually have been sparse impulse response. Impulsive NOISE and sparsity of the acoustic channel are two important challenges in the ANC scenario that have paid special attention, recently. This paper presents a novel adaptive NOISE CANCELLATION algorithm, to address the poor performance of the LMS algorithm in presence of impulsive NOISE along with a sparse impulse response. In order to eliminate impulsive NOISE from speech signal, the information theoretic criterion is used in the proposed cost function and the zero norm is also employed to deal with the sparsity feature of the acoustic channel impulse response. Simulation results indicates the superiority of the proposed algorithm in presence of impulsive NOISE along with sparsity condition of acoustic channel.

A new method for NOISE CANCELLATION of reflected RADAR signal is proposed in this paper. With customary signal processing techniques such as Fourier transform or short time Fourier transform, some signal parameters are extracted. Using Chirplet transform which represent signal in time, frequency, shear, rotation and scale with non-stationary assumption, some signal parameters are estimated. Our presented algorithm is implemented on real RADAR signatures and the result illustrates very good performance in NOISE CANCELLATION of reflected RADAR signal.

In this paper a hybrid ACTIVE DC line conditioner for fluctuations and ripples reduction in voltage and current of DC power systems is proposed. Malfunctions in operation of equipments and systems which are supplied by low quality distribution power systems are one of the main effects of DC voltage ripple. In the proposed configuration a hybrid system including series and shunt ACTIVE line conditioners for ripple reduction of load voltage and source current is used. Simulation and experimental results are provided to show the performance of the proposed configuration in different states.