- Use 32 bits floating point unit, made the operation precision more higher.
- Use 96KHz sampling frequency. Sounds more nicely, less distortion.
- PC long-distance control by using the attached software.
- Wide setting range & adjustable step distance is 1/36 octave.
| DSP-4800 | |
|---|---|
Input |
4 way electronic balance |
Impedance |
>10k Ohms |
Output |
8 way electronic balance |
Frequency response |
±0.5dB 20Hz-20kHz |
Dynamic range |
>100dB 20Hz-20kHz |
Distortion |
<0.2%@1kHz, +18dBm |
The maximum delay |
650mS |
Output/ Input gain |
Setting range: -40dB~+l5dB |
Filter |
8 bands/each output |
Filter gain |
+15dB to -30dB |
Central Frequency |
20Hz-20kHz |
Transition frequency (LF} |
20Hz – 1kHz |
Transition frequency (HF) |
1kHz-20kHz |
Gain |
+l5dB |
Threshold range |
+20dBu to -10dBu |
Start-up time |
0.3 to 90ms |
Release time |
start-up time 4,8,16 or 32 times |
- Use 32 bits floating point unit, made the operation precision more higher.
- Use 96KHz sampling frequency. Sounds more nicely, less distortion.
- PC long-distance control by using the attached software.
- Wide setting range & adjustable step distance is 1/36 octave.
| DSP-2600 | |
|---|---|
Input |
2 way electronic balance |
Impedance |
>10k Ohms |
Output |
6 way electronic balance |
Frequency response |
±0.5dB 20Hz-20kHz |
Dynamic range |
>100dB 20Hz-20kHz |
Distortion |
<0.2%@1kHz, +18dBm |
The maximum delay |
650mS |
Output/ Input gain |
Setting range: -40dB~+l5dB |
Filter |
8 bands/each output |
Filter gain |
+15dB to -30dB |
Central Frequency |
20Hz-20kHz |
Transition frequency (LF} |
20Hz – 1kHz |
Transition frequency (HF) |
1kHz-20kHz |
Gain |
+l5dB |
Threshold range |
+20dBu to -10dBu |
Start-up time |
0.3 to 90ms |
Release time |
start-up time 4,8,16 or 32 times |
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Machine Learning is a subset of AI that focuses on developing algorithms and models that allow computers to learn from data and improve their performance over time. It plays a crucial role in enabling AI systems to recognize patterns, make predictions, and adapt to new information.
Machine Learning is a subset of AI that focuses on developing algorithms and models that allow computers to learn from data and improve their performance over time. It plays a crucial role in enabling AI systems to recognize patterns, make predictions, and adapt to new information.
Machine Learning is a subset of AI that focuses on developing algorithms and models that allow computers to learn from data and improve their performance over time. It plays a crucial role in enabling AI systems to recognize patterns, make predictions, and adapt to new information.
Machine Learning is a subset of AI that focuses on developing algorithms and models that allow computers to learn from data and improve their performance over time. It plays a crucial role in enabling AI systems to recognize patterns, make predictions, and adapt to new information.