IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING

The 8051/8052 microcontroller family is very popular and is found in a huge number of applications in professional systems and amateur projects .This paper describes the design of programming system for the 8051/8052 UV and Flash ROM based microcontrollers that work in conjunction with an IBM style personal computer. The programmer uses the standard parallel printer port operating in bidirectional mode to interface with the host personal computer . An integral power supply and external step down power transformer provides the programmer with all required operating voltages.The programmer is controlled by software written in Visual Basic running on the host personal computer. Two versions of the software were written; the first will run on personal computers that operate under Windows 95, Windows 98, and Windows millennium .The other will run under Windows NT/2000, and Windows XP. This was done because unlike Windows 95 & 98, Windows NT/2000/XP will cause an exception (Privileged Instruction) if an attempt is made to access a port that an application program is privileged to talk to and program execution is halted . This problem was solved by modifying the I/O permission bitmap in system Kernel Mode Driver to allow a particular task, access to certain I/O ports.Hardware and software were designed to support most type of 8051/8052 microcontrollers made by known chip manufactures like Intel, AMD, Philips, Atmel, ST microelectronics , and Cygnal . Upon detecting chip type by reading signature byte, the proper programming voltage, timing, and algorithm suitable for a given chip are chosen automatically by software running on host .The programmer supports all memory microcontroller functions, including signature read, code read , code write, code verification ,chip erase for microcontrollers equipped with flash memory, and lock bit write .

In this paper the performance of speech compression system using discrete wavelet transform (DWT) is investigated .Two methods are used for this purpose ;in the first only discrete wavelet transform is used .In the second method linear predictive coding (LPC) in wavelet transform is used . Both methods are used differential pulse code modulation (DPCM) for quantization with optimum selection of quantization parameters using L1oyd algorithm. Huffman code is used for both methods to increase the compression ratio without effect on the quality performance of speech signal. The results show that DPCM with DWT gives the best performance than when it is used with LPC and DWT. For speech compression using DWT, for n=3 and 4,Db10 gives high quality measure and less CF. For n=1 and 2,Db2 gives better results for compression factor and quality measures. For speech compression using LPC and DWT, Db6 gives good performance .

The main objective of this paper is to apply radial basis function neural networks (RBFNN) and evaluated its performance by comparing the results with other methods. In this paper two feature vectors are used separately to address speaker identification problem. The features are linear predictive code (LPC) and Mel-frequency cepstral coefficient (MFCC).The radial basis function neural network (RBFNN) approach is used for matching purpose.This work proposes can be summarized into three steps. The first step is to frame and windowing the input speech signal using hamming window. The second step is to extract the reference and test speech signal using LPC or MFCC as feature extraction. Finally, in the third step, radial basis function neural network has been used to perform the similarity between the test and reference templates. The results show that speaker identification using MFCC and RBFNN gives (100%) identification rate and higher identification rate compared with other method.

Speech enhancement is an important proceeding which it can be achieved by estimate the clean speech from noisy speech. The clean speech is corrupted by white Gaussian noise . In this paper, thresholding the wavelet coefficients, that can be done by standard deviation method for each frame by level dependent thresholding using semi soft threshold and soft threshold .The results in this work indicate that using wavelet transform in speech enhancement application provides a good quality (measured in object SNR test) as well as provides other advantages which make it more suitable for some application s such as a split of frequencies and enhancement the speech in real time applications .

The last two decades have shown in increasing trend in the use of nanigation technologies such as Strapdown Inertial Systems (SDINS) in several applications including land vehicles and automated car navigation. On the other hand it can cause large position errors over short time, due to the low quality of the Inertial Measurement Unit (IMU). These errors determine the performance and the navigation accuracy of the INSs. Although the huge efforts to improve SDINSin terms of its mechanization equations,it could not cover the remaining drawbacks of SDINS; such as the impact of INS short term errors ,model dependency ,prior knowledge dependency , sensor dependency , and computational errors. This paper proposed an intelligent navigator to overcome the limitation of existing INS algorithms. The intelligent navigator is based on Adaptive Neuro-Fuzzy Inference System (ANFIS). The proposed conceptual intelligent navigator consisted of SDINS architecture that was developed using adaptive fuzzy system networks to acquire the navigation knowledge. In addition, a navigation information Database ,and a window-based learned parameters updating method were implemented to store and accumulate navigation knowledge.

The paper describe approach to the image compression using new hybrid Transforms ,namely, the improvement ridgelet transform that has proven to show promising results over ridgelet transform. The hybrid transform based of replacing the wavelet transform with the slantlet transform, the slantlet transform is a discrete wavelet transform with two zero moments and with improved time localization. A comparison was made with compression using ridgelet transform for different images. A high quality image compression has been achieved for natural images. Computer simulation results indicate that the improvement ridgelet transform offers superior and faster compression performance compared to the ridgelet transform based approaches.

The integration of global positioning system (GPS) and Inertial Navigation System (INS) are continuously gaining interests in many positioning and navigation applications. Both systems have their unique features and shortcomings. Their integration offers systems that overcome each of their drawbacks and maximize each of their benefits. An INS/GPS integration method based on Artificial Neural Networks (ANNs) to fuse INS measurements and GPS measurements has been suggested. It is also provide high performance INS/GPS integration with accurate prediction for position And velocity components during GPS signal absence. Thus the integration of the two systems presents a number of advantages and overcomes each systems inadequacy. An ANN was adopted in this paper using position and velocity update architectures and utilizing the window based weight updating strategy to updates the navigation knowledge in the strategy using two data test IMU systems.

The aim of this article is to find an efficient method to keep the database of critical tasks correct and update for performing the work of real time processing (such as power or water distributed environment), design and implement dual database server to control access to the database so the client read from one of dual server and update, write to both of them, if one of them fail then the other one must be capable of control and access all the client to its database. When the other server return to work the worked server would be responsible for updating this server database. The result shows that, using duality system resolves those problem existing in single server system and eliminates the dependency on the clients in accessing the database ;the existence of a second active server gives continuity for the work and never stopped the clients.

Motion detectors are widely implemented in the design of intruder alarm systems. While these detectors in their raw state can have high detection sensitivity, this comes at the expense of generating higher false alarm rates. The most popular motion detection techniques implement either Passive infrared motion sensors or Active Continuous Wave Microwave Doppler motion sensors. Motion detectors using Dual Detectors employing both Doppler Microwave (MW) and Passive Infrared (PIR) motion sensors provide a new performance level where the feature of both sensors are combined while avoiding the disadvantages of both. The sensors are combined through a microprocessor to provide” intelligent “motion detection system designed to greatly reduce or eliminate “single detector” false alarm. A peripheral Integrated Controller (PIC) based on the popular 8051 device manufactured by Cygnal Corporation the C8051F020 has been chosen in order to reduce designed hardware complexity and utilize the improved features of this device to obtain better system performance. The PIR and Doppler Microwave detection systems are each designed as independent motion detectors. The PIC receives signals from these two sensors in addition to a third signal from a light sensor. The PIC compares the received signals against pre-stored values, double checking their existence in addition to dynamically selecting threshold detection levels depending on weather the motion detection system was operating in day light or at night. The result is a detector with a higher performance in terms of accuracy and detection certainty. The designed system has a large room for continued performance enhancements and features addition that can lead to designing a motion detection system that can fulfill every security system requirement.

In this paper, the structure of the controller is consist s of a Modified Elman Neural Networks MENN model that is learned on-line by using genetic algorithm teachings in order to achieve required yaw rate and reduce lateral velocity in a short period of time to prevent vehicle from sliding out the curvature. By using differential braking system and front wheel steering angle has automatically controlled the vehicle lateral motion when the vehicle rotates the curvatures. The robust feedback neural controller is achieving the excellent transient state output of the system by minimizing the error between the model reference output and the model output of the system. Where the model of the system is also MENN that learned by two stages off-line and on-line, in order to guarantee that the model output accurately represents the actual output of the system by using dynamic Back Propagation Algorithm (BPA).

Estimating the number of sources impinging on an array of sensors is a well known and well investigated problem .A common approach for solving this problem is to use an information theoretic criterion, such as Minimum Description Length (MDL) . MDL technique is very important in many application , but its response degrades under low signal-to-noise ratio (SNR) conditions. This paper proposes a new system to estimate the number of sources by applying MDL to the output of the filter bank consisting quadrature mirror filters (QMF) . Some numerical experiments show that the proposed method can estimate the number of sources under low signal-to-noise ratio(SNR).

Impulse radio ultra wideband (IRI-UWB) communication is becoming an important technology for future wire less Personal Area Networks (WPANs). A critical challenge in IR-UWB system design is multi-user interference (MUI). A RAKE receiver is proposed to mitigate the MUI that occurs in some ad-hoc networks like WPAN for IR-UWB system where concurrent transmission are allowed without power control. The proposed RAKE receiver is shown to contribute to a mitigation of multiple access interference (MAI) especially at medium input bit energy –to-noise ratio (Eb/No) values and small number of RAKE taps (fingers). This receiver is based on chip decision after maximum ratio combining and then the final decision based on the number of pulses per symbols. In such scenarios, the conventional RAKE receiver is completely fails to get the expected BER, and does not always perform well. On the other hand, the proposed RAKE receiver has similar complexity as the conventional RAKE. The binary phase shift keying (BFSK) modulation scheme is used in this paper. The performance of the proposed RAKE is evaluated with the Non Line of sight (NLOS)indoor channel model proposed by the IEEE 802.15.3a (COM3) for WPAN with distances (4-10) m.