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"ABSTRAKPentransmisian sinyal video (video signal) membutuhkan lebar pita frekuensi (bandwidth) dan kapasitas memori yang sangat besar. Untuk mengefisienkan penggunaan bandwidth dan kapasitas memori serta mereduksi biaya transmisi perlu dilakukan proses pemampatan (kompresi) pada sinyal video tersebut. Salah satu teknik kompresi yang banyak digunakan adalah Transform Coding berbasis DCT (Discrete Cosine Transform).Proses transmisi sinyal video dapat dilakukan dengan dua cara yaitu transmisi dengan laju bit yang tetap (Constant Bit Rate/CBR) dan transmisi dengan laju bit yang bervariasi (Variable Bit Rate NBR). CBR digunakan pada proses transmisi menggunakan media transmisi dengan bandwidth yang terbatas, sehingga tidak dapat menampung volume data yang ada. Sedang VBR digunakan pada proses transmisi menggunakan media transmisi dengan bandwidth yang besar sehingga dapat menampung volume data yang ada. Untuk dapat melayani proses transmisi sinyal video VBR diperlukan suatu media transmisi yang mampu memfasilitasi hal tersebut. Salah satunya adalah jaringan ATM (Asynchronous Transfer Mode). Pentransmisian sinyal video VBR melalui jaringan transmisi ATM dilakukan melalui proses pengkodean data pada sinyal video tersebut dan membentuk kode-kode data tersebut ke dalam bentuk struktur sel ATM melalui proses pemaketan (paketisasi).Proses pemaketan dapat dilakukan dengan menggunakan metode Layered Coding yang membagi data-data menjadi dua prioritas yaitu data prioritas tinggi (High Priority Data/HPD) dan data prioritas rendah (Low Priority Data/LPD), dimana data HPD adalah data-data yang mengandung nilai informasi yang terbesar. Kemudian masing-masing data tersebut dibentuk menjadi paket-paket (sel) ATM dan ditransmisikan melalui kanal yang berbeda.Dari simulasi yang dilakukan diperoleh hasil bahwa metode Layered Coding pada pentransmisian sinyal video VBR dapat mempertahankan kualitas gambar yang dikirim dengan mengirimkan data HPD melalui kanal prioritas tinggi (High Priority Channel). Hilangnya (tidak dikirim) data LPD tidak akan berpengaruh besar pada kualitas gambar yang dihasilkan (PSNR 17,2 dB std 26,5 dB), sedangkan hilangnya sebagian kecil (t 1,5%) data HPD akan menimbulkan pengaruh yang besar (degradasi) pada gambar yang dihasilkan (PSNR 8,62 dB).

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ABSTRACTGenerally, wide bandwidth and large memory capacities are needed to transmit the video signal. Using bandwidth and memory capacity efficiently and also reducing the transmission cost, the video signal needs a compression process before transmitted. One of the compression technique which is commonly used is Transform Coding based on DCT (Discrete Cosine Transform).The video signal transmission process could be done in two ways i.e. : constant bit rate (CBR) and variable bit rate (VBR). CBR is a constant rate trans-mission which is used in the transmission process where the bandwidth has incapability to accommodate available data volume. VBR is a variable rate trans-mission which is used in the transmission process where the bandwidth has a capability to accommodate available data volume. ATM (Asynchronous Transfer Mode) network is one of the capable transmission media which is used for transmitting the VBR video signal. The VBR video signal transmission through the ATM network has two processes, coding process and packet process.A Layered Coding method is used for the data packet process. This method divides the data into two priorities i.e.: high priority data (HPD) and low priority data (LPD). The HPD is used for the important data stream and the LPD is used for the rest of the data stream (unimportant data). The data (HPD and LPD) is performed into the ATM cells structure and transmitted through a different channel.The simulation results showed that the layered coding method could maintain the VBR video signal quality by transmitting the HPD through a high priority channel. The lost data of LPD does not annoy the reconstructed video quality (PSNR 17.2 dB - 25.5 dB). The lost data of HPD, however, causes degradation in the quality of the reconstructed video (PSNR 8.62 dB)."

"Physical behavior of models can be measured in the laboratory, which, in turn are often used to assess the behavior of more complicated structures. Mechanical responses present physical behavior of a structure. By using three different transducer, one can measure acceleration, velocity and displacements directly. Determination of velocity and displacements from acceleration data is preferable from point of view economics; but on the other hand this procedure, at present, is still causing problem. This study shows that displacements and velocity can be calculated from its acceleration which is obtained by using one transducer.The acceleration data are obtained from a cantilever steel plate which is subjected to a transient force at a discrete location on its surface or an initial deflection on its tip. An acquisition program was first designed before starting the experimental program. By means of a piezoelectric accelerometer, a conditioning amplifier and a digital oscilloscope, acceleration data are captured and then transferred to a personal computer.The transformation of these two responses, displacements and velocity from the acceleration data are performed in two domains, time domain and frequency domain. Two integration techniques, Newton-Cotes formula and Simpson's rule were used for the calculation in the time domain. For both techniques, adjustment of basis line is performed by End Zero Time Technique Modified. Programmation has been done for both types of domain analysis.The Simpson's rule gives sufficient results and Newton-Cotes formulation gives good results only for moderate values of Cotes coefficient. High values of the coefficient give unrealistic calculated velocity and displacements. Drifting character are present on the displacements calculated by both methods.In the frequency domain, the velocity and displacements are obtained from acceleration data by means of Fast Fourier Transform and its Inverse Fourier Transform. This method give satisfactory results only for the calculation of velocity. The displacements obtained show also drifting character. Nevertheless, realistic forms of this displacements are moderately accepted.Results comparison of the two methods, both in time domain and frequency domain, show that none of the method is better than another. Analysis in frequency domain give more accurate results, but this method is not definitely a principal method for the solution of this type of problems. The two methods shall be used for the calculation of velocity and displacements. This procedure can verify one result to another to avoid wrong interpretation of transformed responses."

"ABSTRAKPendekatan penyelesaian permasalahan dinamika struktur, terutama dalam memperoleh parameter dinamik dapat dilakukan secara numerik atau secara percobaan. Salah satu cara percobaan untuk menjawab masalah tersebut adalah analisis pola percobaan (experimental modal analysis).Pada sepuluh tahun terakhir ini penggunaan komputer personal semakin popular dalam membantu penyelesaian masalah-masalah struktur. Perkembangan analisis pola percobaan didukung pula dengan hal ini. Selain itu, perkembangannya juga dibantu dengan semakin baiknya peralatan elektronik percobaan pendukung analisis pola percobaan tersebut.Pada studi ini dicoba dikembangkan satu perangkat lunak berbasiskan metode penentuan parameter dinamik dalam domain frekuensi untuk analisis pola percobaan. Benda uji yang digunakan adalah satu struktur sederhana yaitu pelat tipis. Parameter sistim dinamik dapat diperoleh secara percobaan dengan melakukan percobaan pola pada pelat tersebut Pelat tersebut mengalami satu eksitasi yang dapat diketahui besarannya dan respons percepatan yang dihasilkan juga dapat diukur. Sistim identifikasi yang menggunakan hasil pengukuran eksitasi dan responsnya membutuhkan satu sistim yang dapat dikontrol dan dapat diobservasi setiap waktu.Cara penentuan parameter dinamik yang digunakan adalah berbasiskan teknik fungsi respons frekuensi. Satu model matematik dipergunakan untuk mempresentasikan sistim fisik dari pelat dimana model tersebut diasumsikan teredam viskos. Dengan mengacu pada keterbatasan kemampuan alat pengukur diasumsikan bahwa titik-titik pengukuran dapat mewakili satu model diskrit dari struktur pelat. Pemakaian akselerometer piezoelektrik, alat pengkondisian, palu dan satu osiloskop digital memungkinkan diperolehnya data percepatan maupun eksitasi; kemudian dengan memakai satu komputer mikro dan program akuisisi yang telah dikembangkan pada penelitian sebelumnya, data tersebut disimpan untuk pengolahan lebih lanjut dengan perangkat lunak yang dikembangkan pada studi ini. Dua program utama dikembangkan dalam studi ini dimana yang pertama untuk mendapatkan fungsi respons frekuensi dari kedua data yang ada dan yang kedua untuk mendapatkan parameter dinamik sistim lewat satu algoritma pencocokan kurva.Pada akhirnya parameter pola yang didapatkan dengan cara diatas dibandingkan dengan hasil yang diperoleh dengan perangkat lunak berbasiskan metode elemen hingga.

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ABSTRACTProcessing of Signal Responses From A Vibrating Structure And Its Application On Thin Plate Problem Structural dynamic problem can be solved with numerical approach or experimental approach. One of the latter method is experimental modal analysis.In the last ten years, the use of personal computer as a tool for solving structural problem became more popular. The development of experimental modal analysis is also influenced by this factor. Another supporting factor is a better quality of experimental instrument.In this study, one program based on the parameter estimation method in the frequency domain is developed. The test structure is a thin plate. Dynamic system parameter can be obtained experimentally by the performance of modal test on the plate. The plate undergoing testing is excited by applying known dynamic forces while the resulting accelerations are measured. System identification utilizing input/output measurement requires the system to be controllable and observable at any time.Dynamic parameter estimation method utilized is based on the frequency response function technique. One mathematical model is used to represent the physical system of the plate. It is assumed that the system is viscously damped. With respect to the performance of measurements it is assumed the measurement points are appropriately distributed to yield a sufficiently accurate discrete model of the test structure.By means of a piezoelectric accelerometer, a conditioning amplifier, an impulse hammer and a digital oscilloscope, accelerations and impulse data are captured and then transferred to a diskette by means of a personal computer and an acquisition program developed in the first year study. Program developed in this study then processes the data in the diskette to obtain dynamic system parameters. Two main routines are developed in this study, the first routine calculates the frequency response function from the two existing data and the second determines the dynamic system parameter by using a curve-fitting algorithm.Finally the modal parameter result obtained are compared to those obtained by a software which is based on the finite element method."

"Dalam teknologi telekomunikasi, pemrosesan sinyal menyandang peran vital. Penerapan teknik tersebut telah merambah ke berbagai bidang seperti halnya bidang pengolahan suara dan ucapan, bidang pengolahan citra, kompresi data, dan estimasi spektral waktu frekuensi.Radar (Radio Detection and Ranging) adalah suatu metode penggunaan gelombang radio untuk mendeteksi kehadiran objek sasaran dan menentukan posisinya (lokasi/jaraknya) serta kecepatannya. Secara umum sinyal echo radar terdiri dari clutter c(t) yang merupakan hamburan dari benda-benda lain, noise n(t) atau derau yang lebih didominasi oleh penerima sendiri (kecuali pada frekuensi rendah), dan sinyal yang mungkin jika ada sasaran.Melalui bentuk pemodelan pembangkitan sinyal echo radar dengan bantuan program berbasiskan Matlab Simulink dan Matlab versi 4.2, maka dapat dianalisa sejauh mana penerapan dari untuk kerja transformasi Wavelet dan membandingkannya dengan transformasi Fourier dalam mengidentifikasi sinyal echo radar . Pemrosesan sinyal ditujukan untuk mengetahui kandungan frekuensi Doppler, dengan kata lain untuk tujuan mengetahui besar kecepatan radial benda terhadap radar. Dalam setiap deteksi diasumsikan selalu ada sasaran yang sudah berhasil dideteksi, sehingga yang harus dilaksanakan adalah mengetahui besar kecepatan radialnya.

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Signal processing plays an important role in communication technology. Application of the technique has broadly expanded to various fields such as sound and utterance processing, image processing, data compression and frequency time spectral estimation.Radar (Radio Detection and Ranging) is one method of using radio wave to detect the targeted objects, their positions (in terms of location and distance) and speeds. Signally radar echo signal consists of clutter c(t), scattering from other objects, noise n(t) or roaring sound, dominantly controlled by the internal receiver (except for low frequency), and possible signal, when the target exist.In form of radar echo signal erection modeling supported with the program-based Matlab Simulink and Matlab Version 4.2, we may analyze application of Wavelet transforms displays as far as possible and compare to the Fourier transforms to identify radar echo signal. Signal processing is aimed at knowing the Doppler frequency ingredients. In other words, it is purposed to see the objects radial speed against the radar. It is assumed that there are always targeted objects already successfully detected. In this care, it is our task to determine the radial speed."

"ABSTRACTDigital signal processing is concerned with the representation of signals by sequences of number or symbols and the processing of the sequences. The purpose of such processing may be to estimate characteristic parameters of a signal or to transform a signal into a form which is in some sense more desirable. The classical numerical analysis formulas, such as those designed for interpolation, integration, and differentiation, are certainly digital signal processing algorithms. The early work on speech and the like - topics still of considerable interest and still the object of active research began less than two decade ago. The rapid development of the subject can be appreciated by scanning the issues of the leading journals. Yet the application of digital signal processing has not been without its problems. It is a field which demands sophisticated technology. "

"The Hidden Markov Model (HMM) is a frequently used tool in scientific research for recognizing pattern. This study discusses sign ature recognition using HMM where the signature image is transmitted from the remote station to the headquarter office by wireless because the remote station was not provided by the original signature as a reference. Generally, the transmission of radio communication has been corrupted with Additive White Gaussian Noise (AWGN) over the Rayleigh fading channel. To reduce the number of bits in the bitstream, the signal prior to transmission was compressed by means of run-length encoding (RLE), also known as source coding. The signature image detected from the receiver was processed in the computer using the HMM. The successful rate of recognition was 0-36% without compression and 60-76%with compression."

"ABSTRAKMetode pensinyalan adalah metode yang mengkodekan bit-bit input menjadi sinyal yang siap djitransmisikan. Contoh dari metode pensinyalan adalah pensinyalan 8-QAM yang merupkan pensinyalan bandpass dan 4B3T yang merupakan penslnyalan baseband Pensinyalan 8-QAM mempakan suatu metode modulasi yang mengkodekan setiap 3 bit menjadi sinyaf yang dimodulasi amplitudo dan fasa carriemya. Sedangkan pensinyalan 4B3T mengkodckan sinyal menjadi 4 big binmy dan-méhtt&x\SmiSikdniiyainié>iijdHi-3`~l-éihabbli(bérdd)°3§ébeigI1i¥§inya}-~3-rér}zki}j». Pada skripsi ini disimulasikan pcrbandingan antara metode pensinyalan 8-QAM dengan metode pensinyalan 4B3T yang memiliki perbandingan periode I baud yang nama. Simulasi yang dilakukan bermjuan untuk mcndapatkan parameter uxquk keljja Bit Error Rate (BER) pada kedua metode.Hasil yang didapat dari simulasi adalah metode 8-QAM memiliki BER yang lebih baik dibandingkm 4B3T pada nilai BER l0`3 dengzm selisih nnai SNR sekimr 6 dB. Dari hasil simujasi dapat dikatakan bahwa unjuk kerja 8-QAM Iebih baik dari 4B3T.

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