TI DSP培训ppt1

The Sum of Products (SOP) is the key element in most DSP algorithms:
Algorithm Finite Impulse Response Filter Equation
y ( n) =
∑a
k =0
M k =0 N
M
k
x(n − k )
We can say that we have a real-time realapplication if:
Waiting Time ≥ 0
Chapter 1, Slide 8
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
C6711 Datasheet: \Links\TMS320C6711.pdf Links\ C6211 Datasheet: \Links\TMS320C6211.pdf Links\
Chapter 1, Slide 13 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why NOT go digital?
High frequency signals cannot be processed digitally because of two reasons:
Analog to Digital Converters, ADC cannot work fast enough. The application can be too complex to be performed in real-time.
Infinite Impulse Response Filter
y ( n) =
∑a
k =0
k
x ( n − k )+
∑b
k =1
N

k
y (n − k )
Convolution
y ( n) =
∑ x ( k ) h( n − k ) ∑ x(n) exp[− j(2π / N )nk ]
n =0 N −1 N −1
Hardware vs. Microcode multiplication
DSP processors are optimised to perform multiplication and addition operations. Multiplication and addition are done in hardware and in one cycle. Example: 4-bit multiply (unsigned). 4Hardware 1011 x 1110 10011010 Microcode 1011 x 1110 0000 1011. 1011.. 1011... 10011010
y (n ) = ∑ a (k )x(n − k )
k =0 99
Chapter 1, Slide 7
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
RealReal-time processing
Waiting Time Processing Time n Sample Time n+1
Resistors. Capacitors. Inductors.
The inherent tolerances associated with these components, temperature, voltage changes and mechanical vibrations can dramatically affect the effectiveness of the analogue circuitry.
Chapter 1, Slide 2 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why go digital?
Digital signal processing techniques are now so powerful that sometimes it is extremely difficult, if not impossible, for analogue signal processing to achieve similar performance. Examples:
Discrete Fourier Transform
X (k ) = F (u ) =
Discrete Cosine Transform
∑
π c(u ). f ( x). cos u (2 x + 1) 2N x =0
Chapter 1, Slide 11
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Parameters to consider when choosing a DSP processor
Parameter I/O bandwidth: Serial Ports (number/speed) DMA channels Multiprocessor support Supply voltage Power management On-chip timers (number/width) Cost Package External memory interface controller JTAG TMS320C6211 (@150MHz) 2 x 75Mbps 16 Not inherent 3.3V I/O, 1.8V Core Yes 2 x 32-bit US$ 21.54 256 Pin BGA Yes Yes TMS320C6711 (@150MHz) 2 x 75Mbps 16 Not inherent 3.3V I/O, 1.8V Core Yes 2 x 32-bit US$ 21.54 256 Pin BGA Yes Yes
Chapter 1 Introduction
Learning Objectives
Why process signals digitally? Definition of a real-time application. realWhy use Digital Signal Processing processors? What are the typical DSP algorithms? Parameters to consider when choosing a DSP processor. Programmable vs ASIC DSP. Texas Instruments’ TMS320 family.
Why do we need DSP processors?
Why not use a General Purpose Processor (GPP) such as a Pentium instead of a DSP processor?
What is the power consumption of a Pentium and a DSP processor? What is the cost of a Pentium and a DSP processor?
Large memory. Advanced operating systems.
Chapter 1, Slide 10 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
What are the typical DSP algorithms?
Parameter Arithmetic format Extended floating point Extended Arithmetic Performance (peak) Number of hardware multipliers Number of registers Internal L1 program memory cache Internal L1 data memory cache Internal L2 cache TMS320C6211 (@150MHz) 32-bit N/A 40-bit 1200MIPS 2 (16 x 16-bit) with 32-bit result 32 32K 32K 512K TMS320C6711 (@150MHz) 32-bit 64-bit 40-bit 1200MFLOPS 2 (32 x 32-bit) with 32 or 64-bit result 32 32K 32K 512K
Cost saving. Smaller size. Low power consumption. Processing of many “high” frequency signals in real-time. real-
Use a GPP processor when the following are required:
FIR filter with linear phase. Adaptive filters.
Chapter 1, Slide 3
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why go digital?
Analogue signal processing is achieved by using analogue components such as:
Chapter 1, Slide 9