Loading...
Search for:
pad--p
1.191 seconds
| # | Type | Title | Author | Publisher | Pub. Year | Subjects | Call Number |
|---|---|---|---|---|---|---|---|
| 1 | مقاله | Design of signature sequences for overloaded CDMA and bounds on the sum capacity with arbitrary symbol alphabets | Alishahi, K. | 2012 |
Multi access channels.
Optimal signature design. Arbitrary distribution. Arbitrary symbols. Asymptotic bounds. CDMA system. Input vector. Large class. Lower and upper bounds. matrix. Maximum likelihood detection. Multi access channel. Optimum detection. Signal to noise. Signature sequences. Spreading gain. Sum capacity. Synchronous CDMA. Synchronous code division multiple access. User data. User symbols. Additive noise. Asymptotic analysis. Matrix algebra. Signal detection. Code division multiple access. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 2 | مقاله | MMSE denoising of sparse and non-gaussian AR(1) processes | Tohidi, P. | Institute of Electrical and Electronics Engineers Inc, | 2016 |
Auto-regressive.
Consistent cycle spinning. De-noising. Message passing. Minimum mean square error. Non-gaussian. Operator-like wavelets. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
| 3 | مقاله | Bounds on the sum capacity of synchronous binary CDMA channels | Alishahi, K. | 2009 |
Binary code-division multiple access (CDMA)
Multiple-access channels (MACs) Multiuser detection (MUD) Sum capacity. Synchronous CDMA. Tight bounds. Additive noise. Binary codes. Control theory. Large scale systems. Multiuser detection. Systems engineering. Code division multiple access. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 4 | مقاله | Errorless codes for CDMA systems with near-far effect | Shafinia, M. H. | 2010 |
CDMA system.
ML decoder. Near-far effects. Near-far resistant. New model. Upper and lower bounds. Very low complexity. Code division multiple access. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 5 | مقاله | New bounds for the sum capacity of binary and nonbinary synchronous CDMA systems | Dashmiz, Sh. | 2010 |
Chip rate.
Lower and upper bounds. matrix. Noisy channel. Non-binary. Sum capacity. Synchronous CDMA. Synchronous CDMA systems. Information theory. Code division multiple access. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 6 | مقاله | New rectangular partitioning methods for lossless binary image compression | Kafashan, M. | 2010 |
Arithmetic encoding.
Binary image compression. Digital image processing. Rectangular partitioning. Adjacent pixels. Compression ratios. High compression ratio. Input image. Lossless. Lossless compression techniques. Partitioning methods. Run-length coding. Text compressions. Binary images. Compression ratio (machinery) Digital arithmetic. Encoding (symbols) Geometry. Image compression. Imaging systems. Pixels. Signal processing. Image coding. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 7 | پایان نامه | کدهای بهینه و ظرفیت کانال در سیستم های CDMA تحت شرایط مختلف Sum Capacity and Optimum Codes of CDMA Systems under Different Conditions | پاد، پدرام Pad, Pedram | صنعتی شریف | 1390 | دسترسی چندگانه با تقسیم کد Code Devision Multiple Access (CDMA) / دسترسی چندگانه Multiple Access / ظرفیت مجموع کانال Sum Channel Capacity / کدهای بهینه Optimum Codes |
05-42118
|
| 8 | مقاله | Almost-optimum signature matrices in binary-input synchronous overloaded CDMA | Khoozani, M. H. | 2011 |
Optimum Capacity Signature Matrices.
Bandwidth limitation. Gaussians. Matrix formation. Multiple access systems. Optimality. Optimum capacity. Overloaded CDMA. Simulation result. Speed-ups. Synchronous CDMA. Welch bound equalities. Wireless communication network. Bit error rate. Channel capacity. Information technology. Optical communication. Wireless telecommunication systems. Code division multiple access. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 9 | مقاله | Capacity achieving linear codes with random binary sparse generating matrices over the binary symmetric channel | Kakhaki, A. M. | IEEE, | 2012 |
Binary erasure channel.
Binary symmetric channel. Block lengths. Channel coding rate. Equal probability. Error exponent. Error probabilities. High probability. Linear codes. Matrix elements. Maximum a posteriori decoders. Probability of errors. Sparse codes. Sparse parity-check matrices. Information theory. Matrix algebra. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
| 10 | مقاله | Constructing and decoding GWBE codes using Kronecker products | Pad, P. | 2010 |
GWBE.
Kronecker product. Maximum likelihood. WBE. GWBE. Kronecker product. Large sizes. Low complexity. Maximum likelihood decoders. Novel methods. Welch bound equalities. Computational complexity. Decoding. Maximum likelihood. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 11 | مقاله | Optimized wavelet denoising for self-similar α-stable processes | Pad, P. | 2017 |
Denoising.
Self-similar processes. A-stable random variables. Calculations. Estimation. Gaussian noise (electronic) Random processes. Shrinkage. Signal processing. Stability criteria. Stochastic systems. Wavelet transforms. White noise. Additive white gaussian noise. Calculus of variations. De-noising. Mean square approximations. Self-similar process. Sparse signal processing. Stable random variables. Statistical parameters. Discrete wavelet transforms. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 12 | مقاله | Simplified MAP-MUD for active user CDMA | Pad, P. | 2011 |
Active user identification.
CDMA. MAP. Viterbi Algorithm. Binary inputs. CDMA system. Maximum A posteriori probabilities. Spreading factor. Two stage. User identification. Variable number of users. Viterbi. Decoding. Multiuser detection. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 13 | مقاله | A class of errorless codes for overloaded synchronous wireless and optical CDMA systems | Pad, P. | 2009 |
Binary code-division multiple-access (CDMA)
Overloaded code-division multiple-access (CDMA) Welch bound equality. Bandwidth reductions. Chip rate. Downlink wireless systems. Fixed numbers. Lower and upper bounds. Maximum likelihood decoder. Maximum likelihood methods. Moderate value. New class. Noisy channel. Optical CDMA. Optical code division multiple access. Simulation result. Upper Bound. Welch bound equality. Welch bound equality sequences. Binary codes. Binary sequences. Block codes. Channel capacity. Code division multiple access. Decoding. Maximum likelihood. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 14 | مقاله | Errorless codes for over-loaded CDMA with active user detection | Pad, P. | 2009 |
Fixed numbers.
ML decoder. Probability of errors. Simulation result. Spreading factor. Upper Bound. User detection. Wireless CDMA. Wireless telecommunication systems. Code division multiple access. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 15 | مقاله | Secrecy capacity scaling in large cooperative wireless networks | Mirmohseni, M. | Institute of Electrical and Electronics Engineers Inc, | 2017 |
Cooperative strategies.
Informationtheoretic security. Large wireless networks. Relaying. Scaling laws. Aggregates. Cooperative communication. Relay control systems. Secure communication. Wireless networks. Colluding eavesdroppers. Cooperative strategy. Information-theoretic security. Secrecy capacity. Network security. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
| 16 | مقاله | Fast estimation of connectivity in fractured reservoirs using percolation theory | Masihi, M. | Society of Petroleum Engineers (SPE), | 2007 |
Anisotropy.
Computer simulation. Flow control. Fracturing fluids. Geometry. Mathematical models. Mechanical permeability. Percolation (fluids) Petroleum geology. Reservoir management. Constant-length isotropic systems. Fracture-length distribution. Fractured reservoir. Petroleum reservoir evaluation. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
| 17 | مقاله | A new decoding scheme for errorless codes for overloaded CDMA with active user detection | Mousavi, A. | 2011 |
Activation/deactivation.
CDMA system. Decoding scheme. Maximum likelihood decoders. Orders of magnitude. User detection. Algorithms. Bit error rate. Decoding. Information technology. Maximum likelihood. Poisson distribution. Telecommunication. Code division multiple access. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
|
| 18 | مقاله | Estimation of the Effective Permeability of Heterogeneous Porous Media by Using Percolation Concepts | Masihi, M. | Springer Netherlands, | 2016 |
Heterogeneity.
High permeability pathway. Percolation theory. Reservoirs. Density functional theory. Mechanical permeability. Percolation (solid state) Petroleum reservoir evaluation. Petroleum reservoirs. Porous materials. Solvents. Characteristic shapes. Effective permeability. Heterogeneous porous media. High permeability. Permeability distribution. Standard algorithms. Petroleum reservoir engineering. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
| 19 | مقاله | Percolation-based effective permeability estimation in real heterogeneous porous media | Masihi, M. | European Association of Geoscientists and Engineers | 2016 |
Oil well flooding.
Porous materials. Solvents. Conductivity measurements. Effective permeability. Heterogeneous media. Heterogeneous porous media. Order of accuracy. Percolating clusters. Permeability contrasts. Power law relation. Estimation. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|
| 20 | مقاله | A novel WaveNet-GRU deep learning model for PEM fuel cells degradation prediction based on transfer learning | Izadi, M. J. | 2024 |
Data-driven method.
Degradation prediction. PEMFC. Cost reduction. Energy efficiency. Forecasting. Learning systems. Mean square error. Proton exchange membrane fuel cells (PEMFC) Data-driven methods. Degradation predictions. GRU. Percentage error. Proton-exchange membranes fuel cells. Remaining useful lives. Root mean square errors. Transfer learning. Voltage prediction. Wavenet. Degradation. Instrumentation. Membrane. Performance assessment. Deep neural networks. |
$stringUtil.getCallnumberViewFormat($resource.getCallNumber())
|