Development of a Chirp Stimulus PC-Based Auditory Brainstem Response Audiometer

Hearing losses during infancy and childhood have many negative future effects and impacts on the child life and productivity. The earlier detection of hearing losses, the earlier medical intervention and then the greater benefit of remediation will be. During this research a PC-based audiometer is designed and, currently, the audiometer prototype is in its final development steps. It is based on the auditory brainstem response (ABR) method. Chirp stimuli instead of traditional click stimuli will be used to invoke the ABR signal. The stimulus is designed to synchronize the hair cells movement when it spreads out over the cochlea. In addition to the available hardware utilization (PC and PCI board), the efforts confined to design and implement a hardware prototype and to develop a software package that enables the system to behave as ABR audiometer. By using such a method and chirp stimulus, it is expected to be able to detect hearing impairment (sensorineural) in the first few days of the life and conduct hearing test at low frequency of stimulus. Currently, the intended chirp stimulus has been successfully generated and the implemented module is able to amplify a signal (on the order of ABR signal) to a recordable level. Moreover, a NI-DAQ data acquisition board has been chosen to implement the PC-prototype interface

Detektor Ml Untuk Komunikasi Antena Jamak

Simple ML Detector for Multiple Antennas Communication System. In order to support providing broadbandwireless communication services against limited and expensive frequency bandwidth, we have to develop a bandwidthefficient system. Therefore, in this paper we propose a closed-loop MIMO (Multiple-Input-Multiple-Output) systemusing ML (Maximum Likelihood) detector to optimize capacity and to increase system performance. What is especiallyexciting about the benefits offered by MIMO is that a high capacity and performance can be attained without additionalfrequency-spectral resource. The grand scenario of this concept is the attained advantages of transformation matriceshaving capability to allocate transmitted signals power suit to the channel. Furthermore, product of these matrices formsparallel singular channels. Due to zero inter-channels correlation, thus we can design ML detector to increase thesystem performance. Finally, computer simulations validates that at 0 dB SNR our system can reach optimal capacityup to 1 bps/Hz and SER up to 0.2 higher than opened-loop MIMO

Model Sinusoida Secara Segmental Untuk Pengkodean Sinyal Suara

Segmental Sinusoidal Model for Speech Signal Coding. Periodic signal can be decomposed by sinusoidal componentwith Fourier series. With this characteristic, it can be modeled referring by sinusoidal form. By the sinusoidal model,signal can be quantized in order to encode the speech signal at the lower rate. The recent sinusoidal method isimplemented in speech coding. By using this method, a block of the speech signal with 20 ms to 30 ms width is codedbased on Fourier series coefficients. The new method proposed is quantization and reconstruction of speech signal bythe segmental sinusoidal model. A segment is defined as a block of the speech signal from certain peak to consecutivepeak. The length of the segment is variable, instead of the fixed block like the recent sinusoidal method. Coder consistsof the encoder and the decoder. Encoder works to code speech signal at variable rate. Then coded signal will betransmitted to receiver. On the receiver, coded signal will be reconstructed, so that the reconstruction signal has the nearquality compared with the original signal. The experimental results show that the average of segmental SNR is morethan 20 dB